From 05bbe55f3930e5bdf5f963539d2de160fe4bd0ef Mon Sep 17 00:00:00 2001 From: Nicholas Clark Date: Thu, 27 Jul 2023 20:39:07 +1000 Subject: [PATCH] update pkgdown site --- docs/pkgdown.yml | 2 +- docs/reference/Rplot001.png | Bin 72586 -> 73247 bytes docs/reference/Rplot002.png | Bin 48364 -> 53916 bytes docs/reference/figures/README-beta_fc-1.png | Bin 17213 -> 17053 bytes docs/reference/figures/README-beta_sim-1.png | Bin 22037 -> 22253 bytes .../figures/README-unnamed-chunk-10-1.png | Bin 24257 -> 21590 bytes .../figures/README-unnamed-chunk-14-1.png | Bin 9483 -> 10062 bytes .../figures/README-unnamed-chunk-15-1.png | Bin 15835 -> 23375 bytes .../figures/README-unnamed-chunk-19-1.png | Bin 8065 -> 8125 bytes .../figures/README-unnamed-chunk-20-1.png | Bin 10378 -> 10622 bytes .../figures/README-unnamed-chunk-21-1.png | Bin 9912 -> 9913 bytes .../figures/README-unnamed-chunk-22-1.png | Bin 7329 -> 7001 bytes .../figures/README-unnamed-chunk-23-1.png | Bin 9718 -> 9414 bytes 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    In addition, the following extended families from the mgcv package are supported:

    • betar for proportional data on (0,1)

    • nb for count data

      • -

    Finally, mvgam supports the three extended families described here:

    • lognormal for non-negative real-valued data

      • +

    Finally, mvgam supports the three extended families described here:

    • lognormal for non-negative real-valued data

    • tweedie for count data (power parameter p fixed at 1.5)

    • student-t for real-valued data

    Note that only poisson(), nb(), and tweedie() are available if diff --git a/docs/reference/mvgam_marginaleffects.html b/docs/reference/mvgam_marginaleffects.html new file mode 100644 index 00000000..056c37eb --- /dev/null +++ b/docs/reference/mvgam_marginaleffects.html @@ -0,0 +1,233 @@ + +Helper functions for mvgam marginaleffects calculations — mvgam_marginaleffects • mvgam + Skip to contents + + +

    +
    +
    +

    Helper functions for mvgam marginaleffects calculations

    + Source: R/marginaleffects.mvgam.R +
    mvgam_marginaleffects.Rd
    +
    + +
    +

    Helper functions for mvgam marginaleffects calculations

    +

    Functions needed for working with marginaleffects

    +

    Functions needed for getting data / objects with insight

    +
    + +
    +

    Usage

    + 
    # S3 method for mvgam
+get_coef(model, trend_effects = FALSE, ...)
+
+# S3 method for mvgam
+set_coef(model, coefs, trend_effects = FALSE, ...)
+
+# S3 method for mvgam
+get_vcov(model, vcov = NULL, ...)
+
+# S3 method for mvgam
+get_predict(
+  model,
+  newdata,
+  type = "response",
+  process_error = FALSE,
+  n_cores = 1,
+  ...
+)
+
+# S3 method for mvgam
+get_data(x, source = "environment", verbose = TRUE, ...)
+
+# S3 method for mvgam
+find_predictors(
+  x,
+  effects = c("fixed", "random", "all"),
+  component = c("all", "conditional", "zi", "zero_inflated", "dispersion", "instruments",
+    "correlation", "smooth_terms"),
+  flatten = FALSE,
+  verbose = TRUE,
+  ...
+)
    +
    + +
    +

    Arguments

    +
    model
    +

    Model object

    + + +
    ...
    +

    Additional arguments are passed to the predict() method +supplied by the modeling package.These arguments are particularly useful +for mixed-effects or bayesian models (see the online vignettes on the +marginaleffects website). Available arguments can vary from model to +model, depending on the range of supported arguments by each modeling +package. See the "Model-Specific Arguments" section of the +?marginaleffects documentation for a non-exhaustive list of available +arguments.

    + + +
    coefs
    +

    vector of coefficients to insert in the model object

    + + +
    vcov
    +

    Type of uncertainty estimates to report (e.g., for robust standard errors). Acceptable values:

    • FALSE: Do not compute standard errors. This can speed up computation considerably.

      • +

    • TRUE: Unit-level standard errors using the default vcov(model) variance-covariance matrix.

      • +

    • String which indicates the kind of uncertainty estimates to return.

      • Heteroskedasticity-consistent: "HC", "HC0", "HC1", "HC2", "HC3", "HC4", "HC4m", "HC5". See ?sandwich::vcovHC

        • +

      • Heteroskedasticity and autocorrelation consistent: "HAC"

        • +

      • Mixed-Models degrees of freedom: "satterthwaite", "kenward-roger"

        • +

      • Other: "NeweyWest", "KernHAC", "OPG". See the sandwich package documentation.

        • +
      • +

    • One-sided formula which indicates the name of cluster variables (e.g., ~unit_id). This formula is passed to the cluster argument of the sandwich::vcovCL function.

      • +

    • Square covariance matrix

      • +

    • Function which returns a covariance matrix (e.g., stats::vcov(model))

      • +
    + + +
    newdata
    +

    Grid of predictor values at which we evaluate the slopes.

    • NULL (default): Unit-level slopes for each observed value in the original dataset. See insight::get_data()

      • +

    • data frame: Unit-level slopes for each row of the newdata data frame.

      • +

    • datagrid() call to specify a custom grid of regressors. For example:

      • newdata = datagrid(cyl = c(4, 6)): cyl variable equal to 4 and 6 and other regressors fixed at their means or modes.

        • +

      • See the Examples section and the datagrid() documentation.

        • +
      • +

    • string:

      • "mean": Marginal Effects at the Mean. Slopes when each predictor is held at its mean or mode.

        • +

      • "median": Marginal Effects at the Median. Slopes when each predictor is held at its median or mode.

        • +

      • "marginalmeans": Marginal Effects at Marginal Means. See Details section below.

        • +

      • "tukey": Marginal Effects at Tukey's 5 numbers.

        • +

      • "grid": Marginal Effects on a grid of representative numbers (Tukey's 5 numbers and unique values of categorical predictors).

        • +
      • +
    + + +
    type
    +

    string indicates the type (scale) of the predictions used to +compute contrasts or slopes. This can differ based on the model +type, but will typically be a string such as: "response", "link", "probs", +or "zero". When an unsupported string is entered, the model-specific list of +acceptable values is returned in an error message. When type is NULL, the +default value is used. This default is the first model-related row in +the marginaleffects:::type_dictionary dataframe.

    + + +
    process_error
    +

    logical. If TRUE, uncertainty in the latent +process (or trend) model is incorporated in predictions

    + + +
    n_cores
    +

    Integer specifying number of cores to use for +generating predictions

    + + +
    x
    +

    A fitted model.

    + + +
    source
    +

    String, indicating from where data should be recovered. If +source = "environment" (default), data is recovered from the environment +(e.g. if the data is in the workspace). This option is usually the fastest +way of getting data and ensures that the original variables used for model +fitting are returned. Note that always the current data is recovered from +the environment. Hence, if the data was modified after model fitting +(e.g., variables were recoded or rows filtered), the returned data may no +longer equal the model data. If source = "frame" (or "mf"), the data +is taken from the model frame. Any transformed variables are back-transformed, +if possible. This option returns the data even if it is not available in +the environment, however, in certain edge cases back-transforming to the +original data may fail. If source = "environment" fails to recover the +data, it tries to extract the data from the model frame; if +source = "frame" and data cannot be extracted from the model frame, data +will be recovered from the environment. Both ways only returns observations +that have no missing data in the variables used for model fitting.

    + + +
    verbose
    +

    Toggle messages and warnings.

    + + +
    effects
    +

    Should model data for fixed effects ("fixed"), random +effects ("random") or both ("all") be returned? Only applies to mixed +or gee models.

    + + +
    component
    +

    Should all predictor variables, predictor variables for the +conditional model, the zero-inflated part of the model, the dispersion +term or the instrumental variables be returned? Applies to models +with zero-inflated and/or dispersion formula, or to models with instrumental +variable (so called fixed-effects regressions). May be abbreviated. Note that the +conditional component is also called count or mean +component, depending on the model.

    + + +
    flatten
    +

    Logical, if TRUE, the values are returned +as character vector, not as list. Duplicated values are removed.

    + +
    +
    +

    Author

    +

    Nicholas J Clark

    +
    + +
    + + +
    +

    Developed by Nicholas J Clark.

    +
    + +
    +

    Site built with pkgdown 2.0.7.

    +
    + +
    + + + + + + + diff --git a/docs/reference/predict.mvgam.html b/docs/reference/predict.mvgam.html index c62e62ca..7d9d53a0 100644 --- a/docs/reference/predict.mvgam.html +++ b/docs/reference/predict.mvgam.html @@ -49,7 +49,15 @@

    Usage

    # S3 method for mvgam
-predict(object, newdata, data_test, type = "link", n_cores = 1, ...)
    +predict( + object, + newdata, + data_test, + type = "link", + process_error = TRUE, + n_cores = 1, + ... +)
    @@ -72,10 +80,18 @@

    ArgumentsValue

    Details

    -

    Note that for all types of predictions, expected uncertainty in the process model is -accounted for only by using draws from the trend SD parameters. If a trend_formula -was supplied in the model, predictions for this component will -also be incorporated. But the trend predictions will ignore autocorrelation +

    Note that for all types of predictions for models that did not include +a trend_formula, uncertainty in the dynamic trend +component can be ignored by setting process_error = FALSE. However, +if a trend_formula was supplied in the model, predictions for this component cannot be +ignored. If process_error = TRUE, trend predictions will ignore autocorrelation coefficients or GP length scale coefficients, ultimately assuming the process is stationary. This method is similar to the types of posterior predictions returned from brms models when using autocorrelated error predictions for newdata. diff --git a/docs/reference/series_to_mvgam.html b/docs/reference/series_to_mvgam.html index 424bb9a4..858852d7 100644 --- a/docs/reference/series_to_mvgam.html +++ b/docs/reference/series_to_mvgam.html @@ -5757,77 +5757,77 @@

    Exampleshead(series) #> gas oil #> 2001-05-01 2 2 -#> 2001-08-01 1 1 -#> 2001-11-01 1 2 -#> 2002-02-01 1 3 -#> 2002-05-01 4 1 -#> 2002-08-01 1 3 +#> 2001-08-01 0 2 +#> 2001-11-01 4 1 +#> 2002-02-01 4 2 +#> 2002-05-01 2 0 +#> 2002-08-01 4 3 series_to_mvgam(series, freq = 4, train_prop = 0.85) #> $data_train #> y season year date series time #> 1 2 2 2001 2001-05-01 gas 1 #> 2 2 2 2001 2001-05-01 oil 1 -#> 3 1 3 2001 2001-08-01 gas 2 -#> 4 1 3 2001 2001-08-01 oil 2 -#> 5 1 4 2001 2001-11-01 gas 3 -#> 6 2 4 2001 2001-11-01 oil 3 -#> 7 1 1 2002 2002-02-01 gas 4 -#> 8 3 1 2002 2002-02-01 oil 4 -#> 9 4 2 2002 2002-05-01 gas 5 -#> 10 1 2 2002 2002-05-01 oil 5 -#> 11 1 3 2002 2002-08-01 gas 6 +#> 3 0 3 2001 2001-08-01 gas 2 +#> 4 2 3 2001 2001-08-01 oil 2 +#> 5 4 4 2001 2001-11-01 gas 3 +#> 6 1 4 2001 2001-11-01 oil 3 +#> 7 4 1 2002 2002-02-01 gas 4 +#> 8 2 1 2002 2002-02-01 oil 4 +#> 9 2 2 2002 2002-05-01 gas 5 +#> 10 0 2 2002 2002-05-01 oil 5 +#> 11 4 3 2002 2002-08-01 gas 6 #> 12 3 3 2002 2002-08-01 oil 6 -#> 13 0 4 2002 2002-11-01 gas 7 +#> 13 3 4 2002 2002-11-01 gas 7 #> 14 1 4 2002 2002-11-01 oil 7 -#> 15 0 1 2003 2003-02-01 gas 8 +#> 15 1 1 2003 2003-02-01 gas 8 #> 16 2 1 2003 2003-02-01 oil 8 -#> 17 3 2 2003 2003-05-01 gas 9 -#> 18 3 2 2003 2003-05-01 oil 9 +#> 17 2 2 2003 2003-05-01 gas 9 +#> 18 2 2 2003 2003-05-01 oil 9 #> 19 0 3 2003 2003-08-01 gas 10 -#> 20 0 3 2003 2003-08-01 oil 10 -#> 21 1 4 2003 2003-11-01 gas 11 +#> 20 1 3 2003 2003-08-01 oil 10 +#> 21 2 4 2003 2003-11-01 gas 11 #> 22 0 4 2003 2003-11-01 oil 11 -#> 23 2 1 2004 2004-02-01 gas 12 -#> 24 0 1 2004 2004-02-01 oil 12 +#> 23 0 1 2004 2004-02-01 gas 12 +#> 24 5 1 2004 2004-02-01 oil 12 #> 25 1 2 2004 2004-05-01 gas 13 -#> 26 1 2 2004 2004-05-01 oil 13 -#> 27 0 3 2004 2004-08-01 gas 14 -#> 28 2 3 2004 2004-08-01 oil 14 +#> 26 0 2 2004 2004-05-01 oil 13 +#> 27 1 3 2004 2004-08-01 gas 14 +#> 28 4 3 2004 2004-08-01 oil 14 #> 29 0 4 2004 2004-11-01 gas 15 -#> 30 2 4 2004 2004-11-01 oil 15 +#> 30 1 4 2004 2004-11-01 oil 15 #> 31 0 1 2005 2005-02-01 gas 16 -#> 32 1 1 2005 2005-02-01 oil 16 +#> 32 0 1 2005 2005-02-01 oil 16 #> 33 1 2 2005 2005-05-01 gas 17 -#> 34 2 2 2005 2005-05-01 oil 17 +#> 34 3 2 2005 2005-05-01 oil 17 #> 35 0 3 2005 2005-08-01 gas 18 -#> 36 0 3 2005 2005-08-01 oil 18 +#> 36 1 3 2005 2005-08-01 oil 18 #> 37 1 4 2005 2005-11-01 gas 19 -#> 38 0 4 2005 2005-11-01 oil 19 +#> 38 1 4 2005 2005-11-01 oil 19 #> 39 1 1 2006 2006-02-01 gas 20 -#> 40 0 1 2006 2006-02-01 oil 20 -#> 41 1 2 2006 2006-05-01 gas 21 -#> 42 4 2 2006 2006-05-01 oil 21 -#> 43 0 3 2006 2006-08-01 gas 22 -#> 44 0 3 2006 2006-08-01 oil 22 +#> 40 3 1 2006 2006-02-01 oil 20 +#> 41 3 2 2006 2006-05-01 gas 21 +#> 42 2 2 2006 2006-05-01 oil 21 +#> 43 2 3 2006 2006-08-01 gas 22 +#> 44 2 3 2006 2006-08-01 oil 22 #> 45 0 4 2006 2006-11-01 gas 23 -#> 46 1 4 2006 2006-11-01 oil 23 +#> 46 0 4 2006 2006-11-01 oil 23 #> 47 1 1 2007 2007-02-01 gas 24 -#> 48 2 1 2007 2007-02-01 oil 24 +#> 48 0 1 2007 2007-02-01 oil 24 #> 49 1 2 2007 2007-05-01 gas 25 #> 50 0 2 2007 2007-05-01 oil 25 #> #> $data_test #> y season year date series time #> 1 0 3 2007 2007-08-01 gas 26 -#> 2 3 3 2007 2007-08-01 oil 26 -#> 3 3 4 2007 2007-11-01 gas 27 -#> 4 2 4 2007 2007-11-01 oil 27 -#> 5 0 1 2008 2008-02-01 gas 28 -#> 6 1 1 2008 2008-02-01 oil 28 -#> 7 0 2 2008 2008-05-01 gas 29 -#> 8 1 2 2008 2008-05-01 oil 29 -#> 9 0 3 2008 2008-08-01 gas 30 -#> 10 3 3 2008 2008-08-01 oil 30 +#> 2 0 3 2007 2007-08-01 oil 26 +#> 3 2 4 2007 2007-11-01 gas 27 +#> 4 0 4 2007 2007-11-01 oil 27 +#> 5 4 1 2008 2008-02-01 gas 28 +#> 6 0 1 2008 2008-02-01 oil 28 +#> 7 3 2 2008 2008-05-01 gas 29 +#> 8 3 2 2008 2008-05-01 oil 29 +#> 9 2 3 2008 2008-08-01 gas 30 +#> 10 1 3 2008 2008-08-01 oil 30 #>

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    @@ -164,7 +164,7 @@

    Arguments max(training timepoints) - fc_horizon model1 list object returned mvgam representing first model evaluated model2 list object returned mvgam representing second model evaluated","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/evaluate_mvgams.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Evaluate forecasts from fitted mvgam objects — evaluate_mvgams","text":"eval_mvgam, list object containing information specific evaluations series (using drps crps score) vector scores using variogram. roll_eval_mvgam, list object containing information specific evaluations series well total evaluation summary (taken summing forecast score series evaluation averaging coverages evaluation) compare_mvgams, series plots comparing forecast Rank Probability Scores competing model. lower score preferred. Note however possible select model ultimately perform poorly true --sample forecasting. example wiggly smooth function 'year' included model function learned prior evaluating rolling window forecasts, model generate tight predictions result. forecasting ahead timepoints model seen (.e. next year), smooth function end extrapolating, sometimes strange unexpected ways. therefore recommended use smooth functions covariates adequately measured data (.e. 'seasonality', example) reduce possible extrapolation smooths let latent trends mvgam model capture temporal dependencies data. trends time series models provide much stable forecasts","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/evaluate_mvgams.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Evaluate forecasts from fitted mvgam objects — evaluate_mvgams","text":"eval_mvgam generates set samples representing fixed parameters estimated full mvgam model latent trend states given point time. trends rolled forward total fc_horizon timesteps according estimated state space dynamics generate '--sample' forecast evaluated true observations horizon window. function therefore simulates situation model's parameters already estimated observed data evaluation timepoint like generate forecasts latent trends observed timepoint. Evaluation involves calculating appropriate Rank Probability Score binary indicator whether true value lies within forecast's 90% prediction interval roll_eval_mvgam sets sequence evaluation timepoints along rolling window iteratively calls eval_mvgam evaluate '--sample' forecasts. Evaluation involves calculating Discrete Rank Probability Score binary indicator whether true value lies within forecast's 90% prediction interval compare_mvgams automates evaluation compare two fitted models using rolling window forecast evaluation provides series summary plots facilitate model selection. essentially wrapper roll_eval_mvgam","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/forecast.mvgam.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract or compute hindcasts and forecasts for a fitted mvgam object — forecast.mvgam","title":"Extract or compute hindcasts and forecasts for a fitted mvgam object — forecast.mvgam","text":"Extract compute hindcasts forecasts fitted mvgam object","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/forecast.mvgam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract or compute hindcasts and forecasts for a fitted mvgam object — forecast.mvgam","text":"","code":"forecast(object, ...) # S3 method for mvgam forecast( object, newdata, data_test, series = \"all\", n_cores = 1, type = \"response\", ... )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/forecast.mvgam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract or compute hindcasts and forecasts for a fitted mvgam object — forecast.mvgam","text":"object list object returned mvgam. See mvgam() ... Ignored newdata Optional dataframe list test data containing least 'series' 'time' addition variables included linear predictor original formula. included, covariate information newdata used generate forecasts fitted model equations. newdata originally included call mvgam, forecasts already produced generative model simply extracted plotted. However newdata supplied original model call, assumption made newdata supplied comes sequentially data supplied data original model (.e. assume time gap last observation series 1 data first observation series 1 newdata) data_test Deprecated. Still works place newdata users recommended use newdata instead seamless integration R workflows series Either integer specifying series set forecast, character string '', specifying series forecast. preferable fitted model contained multivariate trends (either dynamic factor VAR process), saves recomputing full set trends series individually n_cores integer specifying number cores generating forecasts parallel type value link, linear predictor calculated log link scale. response used, predictions take uncertainty observation process account return predictions outcome (discrete) scale (default). trend used, forecast distribution latent trend returned","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/forecast.mvgam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extract or compute hindcasts and forecasts for a fitted mvgam object — forecast.mvgam","text":"object class mvgam_forecast containing hindcast forecast distributions. See mvgam_forecast-class details.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/forecast.mvgam.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Extract or compute hindcasts and forecasts for a fitted mvgam object — forecast.mvgam","text":"Posterior predictions drawn fitted mvgam used simulate forecast distribution","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/get_monitor_pars.html","id":null,"dir":"Reference","previous_headings":"","what":"Return parameters to monitor during modelling — get_monitor_pars","title":"Return parameters to monitor during modelling — get_monitor_pars","text":"Return parameters monitor modelling","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/get_monitor_pars.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return parameters to monitor during modelling — get_monitor_pars","text":"","code":"get_monitor_pars(family, smooths_included = TRUE, use_lv, trend_model, drift)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/get_monitor_pars.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return parameters to monitor during modelling — get_monitor_pars","text":"family character smooths_included Logical. smooth terms included model formula? use_lv Logical (use latent variable trends ) trend_model type trend model used drift Logical (drift term estimated )","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/get_monitor_pars.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Return parameters to monitor during modelling — get_monitor_pars","text":"string parameters monitor","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/get_mvgam_priors.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract information on default prior distributions for an mvgam model — get_mvgam_priors","title":"Extract information on default prior distributions for an mvgam model — get_mvgam_priors","text":"function lists parameters can prior distributions changed given mvgam model, well listing default distributions","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/get_mvgam_priors.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract information on default prior distributions for an mvgam model — get_mvgam_priors","text":"","code":"get_mvgam_priors( formula, trend_formula, data, data_train, family = \"poisson\", use_lv = FALSE, n_lv, use_stan = TRUE, trend_model = \"None\", trend_map, drift = FALSE )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/get_mvgam_priors.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract information on default prior distributions for an mvgam model — get_mvgam_priors","text":"formula character string specifying GAM formula. exactly like formula GLM except smooth terms, s, te, ti t2, can added right hand side specify linear predictor depends smooth functions predictors (linear functionals ) trend_formula optional character string specifying GAM process model formula. supplied, linear predictor modelled latent trends capture process model evolution separately observation model. response variable specified left-hand side formula (.e. valid option ~ season + s(year)). feature experimental, currently available Random Walk trend models. data dataframe list containing model response variable covariates required GAM formula. include columns: 'y' (discrete outcomes; NAs allowed) 'series' (character factor index series IDs) 'time' (numeric index time point observation). variables included linear predictor formula must also present data_train Deprecated. Still works place data users recommended use data instead seamless integration R workflows family family specifying exponential observation family series. Currently supported families : nb() count data poisson() count data tweedie() count data (power parameter p fixed 1.5) gaussian() real-valued data betar() proportional data (0,1) lognormal() non-negative real-valued data student_t() real-valued data Gamma() non-negative real-valued data See mvgam_families details use_lv logical. TRUE, use dynamic factors estimate series' latent trends reduced dimension format. FALSE, estimate independent latent trends series n_lv integer number latent dynamic factors use use_lv == TRUE. >n_series. Defaults arbitrarily min(2, floor(n_series / 2)) use_stan Logical. TRUE rstan installed, model compiled sampled using Hamiltonian Monte Carlo call cmdstan_model , cmdstanr available, call stan. Note functionality still development options available JAGS can used, including: option Tweedie family option dynamic factor trends. However, Stan can estimate Hilbert base approximate Gaussian Processes, much computationally tractable full GPs time series >100 observations, estimation Stan can support latent GP trends estimation JAGS trend_model character specifying time series dynamics latent trend. Options : None (latent trend component; .e. GAM component contributes linear predictor, observation process source error; similarly estimated gam) RW (random walk possible drift) AR1 (possible drift) AR2 (possible drift) AR3 (possible drift) VAR1 (contemporaneously uncorrelated VAR1; available Stan) VAR1cor (contemporaneously correlated VAR1; available Stan) GP (Gaussian Process squared exponential kernel; available Stan) See mvgam_trends details trend_map Optional data.frame specifying series depend latent trends. Useful allowing multiple series depend latent trend process, different observation processes. supplied, latent factor model set setting use_lv = TRUE using mapping set shared trends. Needs column names series trend, integer values trend column state trend series depend . series column single unique entry series data (names perfectly match factor levels series variable data). See examples mvgam details drift logical estimate drift parameter latent trend components. Useful latent trend expected broadly follow non-zero slope. Note latent trend less stationary, drift parameter can become unidentifiable, especially intercept term included GAM linear predictor (default calling jagam). Therefore defaults FALSE","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/get_mvgam_priors.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extract information on default prior distributions for an mvgam model — get_mvgam_priors","text":"either data.frame containing prior definitions (suitable priors can altered user) NULL, indicating priors model can modified mvgam interface","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/get_mvgam_priors.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Extract information on default prior distributions for an mvgam model — get_mvgam_priors","text":"Users can supply model formula, prior fitting model, default priors can inspected altered. make alterations, change contents prior column supplying data.frame mvgam function using argument priors. using Stan backend, users can also modify parameter bounds modifying new_lowerbound /new_upperbound columns. necessary using restrictive distributions parameters, Beta distribution trend sd parameters example (Beta support (0,1)), upperbound 1","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/get_mvgam_priors.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Extract information on default prior distributions for an mvgam model — get_mvgam_priors","text":"prior, new_lowerbound /new_upperbound columns output altered defining user-defined priors mvgam model. Use familiar underlying probabilistic programming language. sanity checks done ensure code legal (.e. check lower bounds smaller upper bounds, example)","code":""},{"path":[]},{"path":"https://nicholasjclark.github.io/mvgam/reference/get_mvgam_priors.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Extract information on default prior distributions for an mvgam model — get_mvgam_priors","text":"Nicholas J Clark","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/get_mvgam_priors.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Extract information on default prior distributions for an mvgam model — get_mvgam_priors","text":"","code":"# Simulate three integer-valued time series library(mvgam) dat <- sim_mvgam(trend_rel = 0.5) # Get a model file that uses default mvgam priors for inspection (not always necessary, # but this can be useful for testing whether your updated priors are written correctly) mod_default <- mvgam(y ~ s(series, bs = 're') + s(season, bs = 'cc') - 1, family = 'nb', data = dat$data_train, trend_model = 'AR2', run_model = FALSE) # Inspect the model file with default mvgam priors mod_default$model_file #> [1] \"\" #> [2] \"// Stan model code generated by package mvgam\" #> [3] \"functions {\" #> [4] \"vector rep_each(vector x, int K) {\" #> [5] \"int N = rows(x);\" #> [6] \"vector[N * K] y;\" #> [7] \"int pos = 1;\" #> [8] \"for (n in 1:N) {\" #> [9] \"for (k in 1:K) {\" #> [10] \"y[pos] = x[n];\" #> [11] \"pos += 1;\" #> [12] \"}\" #> [13] \"}\" #> [14] \"return y;\" #> [15] \"}\" #> [16] \"}\" #> [17] \"data {\" #> [18] \"int total_obs; // total number of observations\" #> [19] \"int n; // number of timepoints per series\" #> [20] \"int n_sp; // number of smoothing parameters\" #> [21] \"int n_series; // number of series\" #> [22] \"int num_basis; // total number of basis coefficients\" #> [23] \"vector[num_basis] zero; // prior locations for basis coefficients\" #> [24] \"matrix[total_obs, num_basis] X; // mgcv GAM design matrix\" #> [25] \"int ytimes[n, n_series]; // time-ordered matrix (which col in X belongs to each [time, series] observation?)\" #> [26] \"matrix[8,8] S1; // mgcv smooth penalty matrix S1\" #> [27] \"int n_nonmissing; // number of nonmissing observations\" #> [28] \"int flat_ys[n_nonmissing]; // flattened nonmissing observations\" #> [29] \"matrix[n_nonmissing, num_basis] flat_xs; // X values for nonmissing observations\" #> [30] \"int obs_ind[n_nonmissing]; // indices of nonmissing observations\" #> [31] \"}\" #> [32] \"parameters {\" #> [33] \"// raw basis coefficients\" #> [34] \"vector[num_basis] b_raw;\" #> [35] \"\" #> [36] \"// random effect variances\" #> [37] \"vector[1] sigma_raw;\" #> [38] \"\" #> [39] \"// random effect means\" #> [40] \"vector[1] mu_raw;\" #> [41] \"\" #> [42] \"// negative binomial overdispersion\" #> [43] \"vector[n_series] phi_inv;\" #> [44] \"\" #> [45] \"// latent trend AR1 terms\" #> [46] \"vector[n_series] ar1;\" #> [47] \"\" #> [48] \"// latent trend AR2 terms\" #> [49] \"vector[n_series] ar2;\" #> [50] \"\" #> [51] \"// latent trend variance parameters\" #> [52] \"vector[n_series] sigma;\" #> [53] \"\" #> [54] \"// latent trends\" #> [55] \"matrix[n, n_series] trend;\" #> [56] \"\" #> [57] \"// smoothing parameters\" #> [58] \"vector[n_sp] lambda;\" #> [59] \"}\" #> [60] \"\" #> [61] \"transformed parameters {\" #> [62] \"// basis coefficients\" #> [63] \"vector[num_basis] b;\" #> [64] \"\" #> [65] \"b[1:8] = b_raw[1:8];\" #> [66] \"b[9:11] = mu_raw[1] + b_raw[9:11] * sigma_raw[1];\" #> [67] \"\" #> [68] \"}\" #> [69] \"\" #> [70] \"model {\" #> [71] \"// prior for random effect population variances\" #> [72] \"sigma_raw ~ exponential(0.5);\" #> [73] \"\" #> [74] \"// prior for random effect population means\" #> [75] \"mu_raw ~ std_normal();\" #> [76] \"\" #> [77] \"// prior for s(season)...\" #> [78] \"b_raw[1:8] ~ multi_normal_prec(zero[1:8],S1[1:8,1:8] * lambda[1]);\" #> [79] \"\" #> [80] \"// prior (non-centred) for s(series)...\" #> [81] \"b_raw[9:11] ~ std_normal();\" #> [82] \"\" #> [83] \"// priors for AR parameters\" #> [84] \"ar1 ~ std_normal();\" #> [85] \"ar2 ~ std_normal();\" #> [86] \"\" #> [87] \"// priors for smoothing parameters\" #> [88] \"lambda ~ normal(10, 25);\" #> [89] \"\" #> [90] \"// priors for overdispersion parameters\" #> [91] \"phi_inv ~ student_t(3, 0, 0.1);\" #> [92] \"\" #> [93] \"// priors for latent trend variance parameters\" #> [94] \"sigma ~ exponential(2);\" #> [95] \"\" #> [96] \"// trend estimates\" #> [97] \"trend[1, 1:n_series] ~ normal(0, sigma);\" #> [98] \"trend[2, 1:n_series] ~ normal(trend[1, 1:n_series] * ar1, sigma);\" #> [99] \"for(s in 1:n_series){\" #> [100] \"trend[3:n, s] ~ normal(ar1[s] * trend[2:(n - 1), s] + ar2[s] * trend[1:(n - 2), s], sigma[s]);\" #> [101] \"}\" #> [102] \"\" #> [103] \"{\" #> [104] \"// likelihood functions\" #> [105] \"vector[n_nonmissing] flat_trends;\" #> [106] \"real flat_phis[n_nonmissing];\" #> [107] \"flat_trends = (to_vector(trend))[obs_ind];\" #> [108] \"flat_phis = to_array_1d(rep_each(phi_inv, n)[obs_ind]);\" #> [109] \"flat_ys ~ neg_binomial_2(\" #> [110] \"exp(append_col(flat_xs, flat_trends) * append_row(b, 1.0)),\" #> [111] \"inv(flat_phis));\" #> [112] \"}\" #> [113] \"}\" #> [114] \"\" #> [115] \"generated quantities {\" #> [116] \"vector[total_obs] eta;\" #> [117] \"matrix[n, n_series] mus;\" #> [118] \"vector[n_sp] rho;\" #> [119] \"vector[n_series] tau;\" #> [120] \"array[n, n_series] int ypred;\" #> [121] \"matrix[n, n_series] phi_vec;\" #> [122] \"vector[n_series] phi;\" #> [123] \"phi = inv(phi_inv);\" #> [124] \"for (s in 1:n_series) {\" #> [125] \"phi_vec[1:n,s] = rep_vector(phi[s], n);\" #> [126] \"}\" #> [127] \"\" #> [128] \"rho = log(lambda);\" #> [129] \"for (s in 1:n_series) {\" #> [130] \"tau[s] = pow(sigma[s], -2.0);\" #> [131] \"}\" #> [132] \"\" #> [133] \"// posterior predictions\" #> [134] \"eta = X * b;\" #> [135] \"for(s in 1:n_series){ \" #> [136] \"mus[1:n, s] = eta[ytimes[1:n, s]] + trend[1:n, s];\" #> [137] \"ypred[1:n, s] = neg_binomial_2_rng(exp(mus[1:n, s]), phi_vec[1:n, s]);\" #> [138] \"}\" #> [139] \"}\" #> [140] \"\" # Look at which priors can be updated in mvgam test_priors <- get_mvgam_priors(y ~ s(series, bs = 're') + s(season, bs = 'cc') - 1, family = 'nb', data = dat$data_train, trend_model = 'AR2') test_priors #> param_name param_length #> 1 vector[n_sp] lambda; 2 #> 2 vector[1] mu_raw; 1 #> 3 vector[1] sigma_raw; 1 #> 4 vector[n_series] ar1; 3 #> 5 vector[n_series] ar2; 3 #> 6 vector[n_series] sigma; 3 #> 7 vector[n_series] phi_inv; 3 #> param_info prior #> 1 s(season) smooth parameters lambda ~ normal(10, 25); #> 2 s(series) pop mean mu_raw ~ std_normal(); #> 3 s(series) pop sd sigma_raw ~ exponential(0.5); #> 4 trend AR1 coefficient ar1 ~ std_normal(); #> 5 trend AR2 coefficient ar2 ~ std_normal(); #> 6 trend sd sigma ~ exponential(2); #> 7 inverse of NB dispsersion phi_inv ~ student_t(3, 0, 0.1); #> example_change new_lowerbound new_upperbound #> 1 lambda ~ exponential(0.83); NA NA #> 2 mu_raw ~ normal(0.76, 0.67); NA NA #> 3 sigma_raw ~ exponential(0.04); NA NA #> 4 ar1 ~ normal(0.25, 0.74); NA NA #> 5 ar2 ~ normal(-0.25, 0.96); NA NA #> 6 sigma ~ exponential(0.41); NA NA #> 7 phi_inv ~ normal(0.75, 0.14); NA NA # Make a few changes; first, change the population mean for the series-level # random intercepts test_priors$prior[2] <- 'mu_raw ~ normal(0.2, 0.5);' # Now use stronger regularisation for the series-level AR2 coefficients test_priors$prior[5] <- 'ar2 ~ normal(0, 0.25);' # Check that the changes are made to the model file without any warnings by # setting 'run_model = FALSE' mod <- mvgam(y ~ s(series, bs = 're') + s(season, bs = 'cc') - 1, family = 'nb', data = dat$data_train, trend_model = 'AR2', priors = test_priors, run_model = FALSE) code(mod) #> // Stan model code generated by package mvgam #> functions { #> vector rep_each(vector x, int K) { #> int N = rows(x); #> vector[N * K] y; #> int pos = 1; #> for (n in 1:N) { #> for (k in 1:K) { #> y[pos] = x[n]; #> pos += 1; #> } #> } #> return y; #> } #> } #> data { #> int total_obs; // total number of observations #> int n; // number of timepoints per series #> int n_sp; // number of smoothing parameters #> int n_series; // number of series #> int num_basis; // total number of basis coefficients #> vector[num_basis] zero; // prior locations for basis coefficients #> matrix[total_obs, num_basis] X; // mgcv GAM design matrix #> int ytimes[n, n_series]; // time-ordered matrix (which col in X belongs to each [time, series] observation?) #> matrix[8,8] S1; // mgcv smooth penalty matrix S1 #> int n_nonmissing; // number of nonmissing observations #> int flat_ys[n_nonmissing]; // flattened nonmissing observations #> matrix[n_nonmissing, num_basis] flat_xs; // X values for nonmissing observations #> int obs_ind[n_nonmissing]; // indices of nonmissing observations #> } #> parameters { #> // raw basis coefficients #> vector[num_basis] b_raw; #> // random effect variances #> vector[1] sigma_raw; #> // random effect means #> vector[1] mu_raw; #> // negative binomial overdispersion #> vector[n_series] phi_inv; #> // latent trend AR1 terms #> vector[n_series] ar1; #> // latent trend AR2 terms #> vector[n_series] ar2; #> // latent trend variance parameters #> vector[n_series] sigma; #> // latent trends #> matrix[n, n_series] trend; #> // smoothing parameters #> vector[n_sp] lambda; #> } #> transformed parameters { #> // basis coefficients #> vector[num_basis] b; #> b[1:8] = b_raw[1:8]; #> b[9:11] = mu_raw[1] + b_raw[9:11] * sigma_raw[1]; #> } #> model { #> // prior for random effect population variances #> sigma_raw ~ exponential(0.5); #> // prior for random effect population means #> mu_raw ~ normal(0.2, 0.5); #> // prior for s(season)... #> b_raw[1:8] ~ multi_normal_prec(zero[1:8],S1[1:8,1:8] * lambda[1]); #> // prior (non-centred) for s(series)... #> b_raw[9:11] ~ std_normal(); #> // priors for AR parameters #> ar1 ~ std_normal(); #> ar2 ~ normal(0, 0.25); #> // priors for smoothing parameters #> lambda ~ normal(10, 25); #> // priors for overdispersion parameters #> phi_inv ~ student_t(3, 0, 0.1); #> // priors for latent trend variance parameters #> sigma ~ exponential(2); #> // trend estimates #> trend[1, 1:n_series] ~ normal(0, sigma); #> trend[2, 1:n_series] ~ normal(trend[1, 1:n_series] * ar1, sigma); #> for(s in 1:n_series){ #> trend[3:n, s] ~ normal(ar1[s] * trend[2:(n - 1), s] + ar2[s] * trend[1:(n - 2), s], sigma[s]); #> } #> { #> // likelihood functions #> vector[n_nonmissing] flat_trends; #> real flat_phis[n_nonmissing]; #> flat_trends = (to_vector(trend))[obs_ind]; #> flat_phis = to_array_1d(rep_each(phi_inv, n)[obs_ind]); #> flat_ys ~ neg_binomial_2( #> exp(append_col(flat_xs, flat_trends) * append_row(b, 1.0)), #> inv(flat_phis)); #> } #> } #> generated quantities { #> vector[total_obs] eta; #> matrix[n, n_series] mus; #> vector[n_sp] rho; #> vector[n_series] tau; #> array[n, n_series] int ypred; #> matrix[n, n_series] phi_vec; #> vector[n_series] phi; #> phi = inv(phi_inv); #> for (s in 1:n_series) { #> phi_vec[1:n,s] = rep_vector(phi[s], n); #> } #> rho = log(lambda); #> for (s in 1:n_series) { #> tau[s] = pow(sigma[s], -2.0); #> } #> // posterior predictions #> eta = X * b; #> for(s in 1:n_series){ #> mus[1:n, s] = eta[ytimes[1:n, s]] + trend[1:n, s]; #> ypred[1:n, s] = neg_binomial_2_rng(exp(mus[1:n, s]), phi_vec[1:n, s]); #> } #> } # No warnings, the model is ready for fitting now in the usual way with the addition # of the 'priors' argument # Look at what is returned when an incorrect spelling is used test_priors$prior[5] <- 'ar2_bananas ~ normal(0, 0.25);' mod <- mvgam(y ~ s(series, bs = 're') + s(season, bs = 'cc') - 1, family = 'nb', data = dat$data_train, trend_model = 'AR2', priors = test_priors, run_model = FALSE) #> Warning: no match found in model_file for parameter: ar2_bananas code(mod) #> // Stan model code generated by package mvgam #> functions { #> vector rep_each(vector x, int K) { #> int N = rows(x); #> vector[N * K] y; #> int pos = 1; #> for (n in 1:N) { #> for (k in 1:K) { #> y[pos] = x[n]; #> pos += 1; #> } #> } #> return y; #> } #> } #> data { #> int total_obs; // total number of observations #> int n; // number of timepoints per series #> int n_sp; // number of smoothing parameters #> int n_series; // number of series #> int num_basis; // total number of basis coefficients #> vector[num_basis] zero; // prior locations for basis coefficients #> matrix[total_obs, num_basis] X; // mgcv GAM design matrix #> int ytimes[n, n_series]; // time-ordered matrix (which col in X belongs to each [time, series] observation?) #> matrix[8,8] S1; // mgcv smooth penalty matrix S1 #> int n_nonmissing; // number of nonmissing observations #> int flat_ys[n_nonmissing]; // flattened nonmissing observations #> matrix[n_nonmissing, num_basis] flat_xs; // X values for nonmissing observations #> int obs_ind[n_nonmissing]; // indices of nonmissing observations #> } #> parameters { #> // raw basis coefficients #> vector[num_basis] b_raw; #> // random effect variances #> vector[1] sigma_raw; #> // random effect means #> vector[1] mu_raw; #> // negative binomial overdispersion #> vector[n_series] phi_inv; #> // latent trend AR1 terms #> vector[n_series] ar1; #> // latent trend AR2 terms #> vector[n_series] ar2; #> // latent trend variance parameters #> vector[n_series] sigma; #> // latent trends #> matrix[n, n_series] trend; #> // smoothing parameters #> vector[n_sp] lambda; #> } #> transformed parameters { #> // basis coefficients #> vector[num_basis] b; #> b[1:8] = b_raw[1:8]; #> b[9:11] = mu_raw[1] + b_raw[9:11] * sigma_raw[1]; #> } #> model { #> // prior for random effect population variances #> sigma_raw ~ exponential(0.5); #> // prior for random effect population means #> mu_raw ~ normal(0.2, 0.5); #> // prior for s(season)... #> b_raw[1:8] ~ multi_normal_prec(zero[1:8],S1[1:8,1:8] * lambda[1]); #> // prior (non-centred) for s(series)... #> b_raw[9:11] ~ std_normal(); #> // priors for AR parameters #> ar1 ~ std_normal(); #> ar2 ~ std_normal(); #> // priors for smoothing parameters #> lambda ~ normal(10, 25); #> // priors for overdispersion parameters #> phi_inv ~ student_t(3, 0, 0.1); #> // priors for latent trend variance parameters #> sigma ~ exponential(2); #> // trend estimates #> trend[1, 1:n_series] ~ normal(0, sigma); #> trend[2, 1:n_series] ~ normal(trend[1, 1:n_series] * ar1, sigma); #> for(s in 1:n_series){ #> trend[3:n, s] ~ normal(ar1[s] * trend[2:(n - 1), s] + ar2[s] * trend[1:(n - 2), s], sigma[s]); #> } #> { #> // likelihood functions #> vector[n_nonmissing] flat_trends; #> real flat_phis[n_nonmissing]; #> flat_trends = (to_vector(trend))[obs_ind]; #> flat_phis = to_array_1d(rep_each(phi_inv, n)[obs_ind]); #> flat_ys ~ neg_binomial_2( #> exp(append_col(flat_xs, flat_trends) * append_row(b, 1.0)), #> inv(flat_phis)); #> } #> } #> generated quantities { #> vector[total_obs] eta; #> matrix[n, n_series] mus; #> vector[n_sp] rho; #> vector[n_series] tau; #> array[n, n_series] int ypred; #> matrix[n, n_series] phi_vec; #> vector[n_series] phi; #> phi = inv(phi_inv); #> for (s in 1:n_series) { #> phi_vec[1:n,s] = rep_vector(phi[s], n); #> } #> rho = log(lambda); #> for (s in 1:n_series) { #> tau[s] = pow(sigma[s], -2.0); #> } #> // posterior predictions #> eta = X * b; #> for(s in 1:n_series){ #> mus[1:n, s] = eta[ytimes[1:n, s]] + trend[1:n, s]; #> ypred[1:n, s] = neg_binomial_2_rng(exp(mus[1:n, s]), phi_vec[1:n, s]); #> } #> }"},{"path":"https://nicholasjclark.github.io/mvgam/reference/hindcast.mvgam.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract hindcasts for a fitted mvgam object — hindcast.mvgam","title":"Extract hindcasts for a fitted mvgam object — hindcast.mvgam","text":"Extract hindcasts fitted mvgam object","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/hindcast.mvgam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract hindcasts for a fitted mvgam object — hindcast.mvgam","text":"","code":"hindcast(object, ...) # S3 method for mvgam hindcast(object, series = \"all\", type = \"response\", ...)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/hindcast.mvgam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract hindcasts for a fitted mvgam object — hindcast.mvgam","text":"object list object returned mvgam. See mvgam() ... Ignored series Either integer specifying series set forecast, character string '', specifying series forecast. preferable fitted model contained multivariate trends (either dynamic factor VAR process), saves recomputing full set trends series individually type value link, linear predictor calculated log link scale. response used, predictions take uncertainty observation process account return predictions outcome (discrete) scale (default). trend used, hindcast distribution latent trend returned","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/hindcast.mvgam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extract hindcasts for a fitted mvgam object — hindcast.mvgam","text":"object class mvgam_forecast containing hindcast distributions. See mvgam_forecast-class details.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/hindcast.mvgam.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Extract hindcasts for a fitted mvgam object — hindcast.mvgam","text":"Posterior retrodictions drawn fitted mvgam organized convenient format","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/index-mvgam.html","id":null,"dir":"Reference","previous_headings":"","what":"Index mvgam objects — index-mvgam","title":"Index mvgam objects — index-mvgam","text":"Index mvgam objects","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/index-mvgam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Index mvgam objects — index-mvgam","text":"","code":"# S3 method for mvgam variables(x, ...)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/index-mvgam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Index mvgam objects — index-mvgam","text":"x list object class mvgam ... Arguments passed individual methods (applicable).","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/lfo_cv.mvgam.html","id":null,"dir":"Reference","previous_headings":"","what":"Approximate leave-future-out cross-validation of fitted mvgam objects — lfo_cv.mvgam","title":"Approximate leave-future-out cross-validation of fitted mvgam objects — lfo_cv.mvgam","text":"Approximate leave-future-cross-validation fitted mvgam objects","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/lfo_cv.mvgam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Approximate leave-future-out cross-validation of fitted mvgam objects — lfo_cv.mvgam","text":"","code":"lfo_cv(object, ...) # S3 method for mvgam lfo_cv( object, data, min_t, fc_horizon = 1, pareto_k_threshold = 0.7, n_cores = 1, ... )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/lfo_cv.mvgam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Approximate leave-future-out cross-validation of fitted mvgam objects — lfo_cv.mvgam","text":"object list object returned mvgam. See mvgam() ... Ignored data dataframe list containing model response variable covariates required GAM formula. include columns: 'series' (character factor index series IDs) 'time' (numeric index time point observation). variables included linear predictor formula must also present min_t Integer specifying minimum training time required making predictions data. Default either 30, whatever training time allows least 10 lfo-cv calculations (.e. pmin(max(data$time) - 10, 30)) fc_horizon Integer specifying number time steps ahead evaluating forecasts pareto_k_threshold Proportion specifying threshold Pareto shape parameter considered unstable, triggering model refit. Default 0.7 n_cores integer specifying number cores calculating likelihoods parallel","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/lfo_cv.mvgam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Approximate leave-future-out cross-validation of fitted mvgam objects — lfo_cv.mvgam","text":"list class mvgam_lfo containing approximate ELPD scores, Pareto-k shape values 'specified pareto_k_threshold","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/lfo_cv.mvgam.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Approximate leave-future-out cross-validation of fitted mvgam objects — lfo_cv.mvgam","text":"Approximate leave-future-cross-validation uses expanding training window scheme evaluate model forecasting ability. steps used function mirror laid lfo vignette loo package, written Paul Bürkner, Jonah Gabry, Aki Vehtari. First, refit model using first min_t observations perform single exact fc_horizon-ahead forecast step. forecast evaluated min_t + fc_horizon sample observations using Expected Log Predictive Density (ELPD). Next, approximate successive round expanding window forecasts moving forward one step time 1:N_evaluations re-weighting draws model's posterior predictive distribution using Pareto Smoothed Importance Sampling (PSIS). iteration , PSIS weights obtained next observation included model re-fit (.e. last observation training data, min_t + ). importance ratios stable, consider approximation adequate use re-weighted posterior's forecast evaluating next holdout set testing observations ((min_t + + 1):(min_t + + fc_horizon)). point importance ratio variability become large importance sampling fail. indicated estimated shape parameter k generalized Pareto distribution crossing certain threshold pareto_k_threshold. refit model using observations time failure. restart process iterate forward next refit triggered (Bürkner et al. 2020).","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/lfo_cv.mvgam.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Approximate leave-future-out cross-validation of fitted mvgam objects — lfo_cv.mvgam","text":"Paul-Christian Bürkner, Jonah Gabry & Aki Vehtari (2020). Approximate leave-future-cross-validation Bayesian time series models Journal Statistical Computation Simulation. 90:14, 2499-2523.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/lfo_cv.mvgam.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Approximate leave-future-out cross-validation of fitted mvgam objects — lfo_cv.mvgam","text":"Nicholas J Clark","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/logLik.mvgam.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute pointwise Log-Likelihoods from fitted mvgam objects — logLik.mvgam","title":"Compute pointwise Log-Likelihoods from fitted mvgam objects — logLik.mvgam","text":"Compute pointwise Log-Likelihoods fitted mvgam objects","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/logLik.mvgam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute pointwise Log-Likelihoods from fitted mvgam objects — logLik.mvgam","text":"","code":"# S3 method for mvgam logLik(object, n_cores = 1, ...)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/logLik.mvgam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute pointwise Log-Likelihoods from fitted mvgam objects — logLik.mvgam","text":"object list object returned mvgam n_cores integer specifying number cores calculating likelihoods parallel ... Ignored","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/logLik.mvgam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute pointwise Log-Likelihoods from fitted mvgam objects — logLik.mvgam","text":"matrix dimension n_samples x n_observations containing pointwise log-likelihood draws observations (training observations , supplied original model via newdata argument mvgam, testing observations)","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/lv_correlations.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate trend correlations based on mvgam latent factor loadings — lv_correlations","title":"Calculate trend correlations based on mvgam latent factor loadings — lv_correlations","text":"function uses samples latent trends series fitted mvgam model calculates correlations among series' trends","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/lv_correlations.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate trend correlations based on mvgam latent factor loadings — lv_correlations","text":"","code":"lv_correlations(object)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/lv_correlations.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate trend correlations based on mvgam latent factor loadings — lv_correlations","text":"object list object returned mvgam","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/lv_correlations.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate trend correlations based on mvgam latent factor loadings — lv_correlations","text":"list object containing mean posterior correlations full array posterior correlations","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam-class.html","id":null,"dir":"Reference","previous_headings":"","what":"Fitted mvgam object description — mvgam-class","title":"Fitted mvgam object description — mvgam-class","text":"fitted mvgam object returned function mvgam. Run methods(class = \"mvgam\") see overview available methods.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam-class.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Fitted mvgam object description — mvgam-class","text":"mvgam object contains following elements: call original observation model formula trend_call trend_formula supplied, original trend model formula returned. Otherwise NULL family character description observation distribution trend_model character description latent trend model trend_map data.frame describing mapping trend states observations, supplied original model. Otherwise NULL drift Logical specifying whether drift term used trend model priors model priors updated defaults, prior dataframe returned. Otherwise NULL model_output MCMC object returned fitting engine. model fitted using Stan, object class stanfit (see stanfit-class details). JAGS used backend, object class runjags (see runjags-class details) model_file character string model file used describe model either Stan JAGS syntax model_data return_model_data set TRUE fitting model, list object containing data objects needed condition model returned. item list described detail top model_file. Otherwise NULL inits return_model_data set TRUE fitting model, initial value functions used initialise MCMC chains returned. Otherwise NULL monitor_pars parameters monitored MCMC sampling returned character vector sp_names character vector specifying names smoothing parameter mgcv_model object class gam containing mgcv version observation model. object used generating linear predictor matrix making predictions new data. coefficients model object contain posterior median coefficients GAM linear predictor, used generating plots smooth functions mvgam currently handle (plots three-dimensional smooths). model therefore used inference. See gamObject details trend_mgcv_model trend_formula supplied, object class gam containing mgcv version trend model. Otherwise NULL ytimes matrix object used model fitting indexing series timepoints observed row supplied data. Used internally downstream plotting prediction functions resids named list object containing posterior draws Dunn-Smyth randomized quantile residuals use_lv Logical flag indicating whether latent dynamic factors used model n_lv use_lv == TRUE, number latent dynamic factors used model upper_bounds bounds supplied original model fit, returned. Otherwise NULL obs_data original data object (either list dataframe) supplied model fitting. test_data test data supplied (argument newdata original model), returned. Othwerise NULL fit_engine Character describing fit engine, either stan jags max_treedepth model fitted using Stan, value supplied maximum treedepth tuning parameter returned (see stan details). Otherwise NULL adapt_delta model fitted using Stan, value supplied adapt_delta tuning parameter returned (see stan details). Otherwise NULL","code":""},{"path":[]},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam-class.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Fitted mvgam object description — mvgam-class","text":"Nicholas J Clark","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam.html","id":null,"dir":"Reference","previous_headings":"","what":"Fit a Bayesian dynamic GAM to a univariate or multivariate set of discrete time series — mvgam","title":"Fit a Bayesian dynamic GAM to a univariate or multivariate set of discrete time series — mvgam","text":"function estimates posterior distribution Generalised Additive Models (GAMs) can include smooth spline functions, specified GAM formula, well latent temporal processes, specified trend_model. currently two options specifying structures trends (either latent dynamic factors capture trend dependencies among series reduced dimension format, independent trends)","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Fit a Bayesian dynamic GAM to a univariate or multivariate set of discrete time series — mvgam","text":"","code":"mvgam( formula, trend_formula, knots, trend_knots, data, data_train, newdata, data_test, run_model = TRUE, prior_simulation = FALSE, return_model_data = FALSE, family = \"poisson\", use_lv = FALSE, n_lv, trend_map, trend_model = \"None\", drift = FALSE, chains = 4, burnin = 500, samples = 500, thin = 1, parallel = TRUE, threads = 1, priors, upper_bounds, refit = FALSE, use_stan = TRUE, max_treedepth, adapt_delta, jags_path )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Fit a Bayesian dynamic GAM to a univariate or multivariate set of discrete time series — mvgam","text":"formula character string specifying GAM observation model formula. exactly like formula GLM except smooth terms, s, te, ti t2, can added right hand side specify linear predictor depends smooth functions predictors (linear functionals ). trend_formula optional character string specifying GAM process model formula. supplied, linear predictor modelled latent trends capture process model evolution separately observation model. response variable specified left-hand side formula (.e. valid option ~ season + s(year)). feature experimental, currently available Random Walk trend models. knots optional list containing user specified knot values used basis construction. bases user simply supplies knots used, must match k value supplied (note number knots always just k). Different terms can use different numbers knots, unless share covariate. trend_knots knots , optional list knot values smooth functions within trend_formula data dataframe list containing model response variable covariates required GAM formula. include columns: series (character factor index series IDs) time (numeric index time point observation). variables included linear predictor formula must also present data_train Deprecated. Still works place data users recommended use data instead seamless integration R workflows newdata Optional dataframe list test data containing least 'series' 'time' addition variables included linear predictor formula. included, observations variable y set NA fitting model posterior simulations can obtained data_test Deprecated. Still works place newdata users recommended use newdata instead seamless integration R workflows run_model logical. FALSE, model fitted instead function return model file data / initial values needed fit model outside mvgam prior_simulation logical. TRUE, observations fed model, instead simulations prior distributions returned return_model_data logical. TRUE, list data needed fit model returned, along initial values smooth AR parameters, model fitted. helpful users wish modify model file add stochastic elements currently avaiable mvgam. Default FALSE reduce size returned object, unless run_model == FALSE family family specifying exponential observation family series. Currently supported families : nb() count data poisson() count data tweedie() count data (power parameter p fixed 1.5) gaussian() real-valued data betar() proportional data (0,1) lognormal() non-negative real-valued data student_t() real-valued data Gamma() non-negative real-valued data See mvgam_families details use_lv logical. TRUE, use dynamic factors estimate series' latent trends reduced dimension format. FALSE, estimate independent latent trends series n_lv integer number latent dynamic factors use use_lv == TRUE. >n_series. Defaults arbitrarily min(2, floor(n_series / 2)) trend_map Optional data.frame specifying series depend latent trends. Useful allowing multiple series depend latent trend process, different observation processes. supplied, latent factor model set setting use_lv = TRUE using mapping set shared trends. Needs column names series trend, integer values trend column state trend series depend . series column single unique entry series data (names perfectly match factor levels series variable data). See examples details trend_model character specifying time series dynamics latent trend. Options : None (latent trend component; .e. GAM component contributes linear predictor, observation process source error; similarly estimated gam) RW (random walk possible drift) AR1 (possible drift) AR2 (possible drift) AR3 (possible drift) VAR1 (contemporaneously uncorrelated VAR1; available Stan) VAR1cor (contemporaneously correlated VAR1; available Stan) GP (Gaussian Process squared exponential kernel; available Stan) See mvgam_trends details drift logical estimate drift parameter latent trend components. Useful latent trend expected broadly follow non-zero slope. Note latent trend less stationary, drift parameter can become unidentifiable, especially intercept term included GAM linear predictor (default calling jagam). Drift parameters also likely unidentifiable using dynamic factor models. Therefore defaults FALSE chains integer specifying number parallel chains model burnin integer specifying number warmup iterations Markov chain run tune sampling algorithms samples integer specifying number post-warmup iterations Markov chain run sampling posterior distribution thin Thinning interval monitors parallel logical specifying whether multiple cores used generating MCMC simulations parallel. TRUE, number cores use min(c(chains, parallel::detectCores() - 1)) threads integer Experimental option use multithreading within-chain parallelisation Stan. recommend use experienced Stan's reduce_sum function slow running model sped means. available using Cmdstan backend priors optional data.frame prior definitions (JAGS Stan syntax). See get_mvgam_priors 'Details' information changing default prior distributions upper_bounds Optional vector integer values specifying upper limits series. supplied, generates modified likelihood values bound given likelihood zero. Note modification computationally expensive JAGS can lead better estimates true bounds exist. Default remove truncation entirely (.e. upper bound series). Currently implemented Stan refit Logical indicating whether refit, called using update.mvgam. Users leave FALSE use_stan Logical. TRUE rstan installed, model compiled sampled using Hamiltonian Monte Carlo call cmdstan_model , cmdstanr available, call stan. Note many options using Stan vs JAGS (\"advantage\" JAGS ability use Tweedie family). max_treedepth positive integer placing cap number simulation steps evaluated iteration use_stan == TRUE. Default 12. Increasing value can sometimes help exploration complex posterior geometries, rarely fruitful go max_treedepth 14 adapt_delta positive numeric 0 1 defining target average proposal acceptance probability Stan's adaptation period, use_stan == TRUE. Default 0.8. general need change adapt_delta unless see warning message divergent transitions, case can increase adapt_delta default value closer 1 (e.g. 0.95 0.99, 0.99 0.999, etc). step size used numerical integrator function adapt_delta increasing adapt_delta result smaller step size fewer divergences. Increasing adapt_delta typically result slower sampler, always lead robust sampler. jags_path Optional character vector specifying path location JAGS executable (.exe) use modelling use_stan == FALSE. missing, path recovered call findjags","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Fit a Bayesian dynamic GAM to a univariate or multivariate set of discrete time series — mvgam","text":"list object class mvgam containing model output, text representation model file, mgcv model output (easily generating simulations unsampled covariate values), Dunn-Smyth residuals series key information needed functions package. See mvgam-class details.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Fit a Bayesian dynamic GAM to a univariate or multivariate set of discrete time series — mvgam","text":"Dynamic GAMs useful wish predict future values time series show temporal dependence want rely extrapolating smooth term (can sometimes lead unpredictable unrealistic behaviours). addition, smooths can often try wiggle excessively capture autocorrelation present time series, exacerbates problem forecasting ahead. GAMs naturally viewed Bayesian lens, often must model time series show complex distributional features missing data, parameters mvgam models estimated Bayesian framework using Markov Chain Monte Carlo. Priors: jagam model file generated formula modified include latent temporal processes. Prior distributions important model parameters can altered user inspect model sensitivities given priors (see get_mvgam_priors details). Note latent trends estimated log scale choose tau, AR phi priors accordingly. However control model specification can accomplished first using mvgam baseline, editing returned model accordingly. model file can edited run outside mvgam setting run_model = FALSE encouraged complex modelling tasks. Note, priors formally checked ensure right syntax respective probabilistic modelling framework, user ensure correct (.e. use dnorm normal densities JAGS, mean precision parameterisation; use normal normal densities Stan, mean standard deviation parameterisation) Random effects: smooth terms using random effect basis (smooth.construct.re.smooth.spec), non-centred parameterisation automatically employed avoid degeneracies common hierarchical models. Note however centred versions may perform better series particularly informative, foray Bayesian modelling, worth building understanding model's assumptions limitations following principled workflow. Also note models parameterised using drop.unused.levels = FALSE jagam ensure predictions can made levels supplied factor variable Overdispersion parameters: one series included data_train overdispersed exponential family used, additional observation family parameters (.e. phi nb() sigma gaussian()) estimated independently series. Factor regularisation: using dynamic factor model trends JAGS factor precisions given regularized penalty priors theoretically allow factors dropped model squeezing increasing factors' variances zero. done help protect selecting many latent factors needed capture dependencies data, can often advantageous set n_lv slightly larger number. However larger numbers factors come additional computational costs balanced well. using Stan, factors parameterised sd = 0.1 Residuals: series, randomized quantile (.e. Dunn-Smyth) residuals calculated inspecting model diagnostics fitted model appropriate Dunn-Smyth residuals standard normal distribution autocorrelation evident. particular observation missing, residual calculated comparing independent draws model's posterior distribution Using Stan: mvgam primarily designed use Hamiltonian Monte Carlo parameter estimation via software Stan (using either cmdstanr rstan interface). great advantages using Stan Gibbs / Metropolis Hastings samplers, includes option estimate smooth latent trends via Hilbert space approximate Gaussian Processes. often makes sense ecological series, expect change smoothly. mvgam, latent squared exponential GP trends approximated using default 40 basis functions, saves computational costs compared fitting full GPs adequately estimating GP alpha rho parameters. many advantages Stan JAGS, development package applied Stan. includes planned addition response distributions, plans handle zero-inflation, plans incorporate greater variety trend models. Users strongly encouraged opt Stan JAGS proceeding workflows","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Fit a Bayesian dynamic GAM to a univariate or multivariate set of discrete time series — mvgam","text":"Nicholas J Clark & Konstans Wells (2020). Dynamic generalised additive models (DGAMs) forecasting discrete ecological time series. Methods Ecology Evolution. 14:3, 771-784.","code":""},{"path":[]},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Fit a Bayesian dynamic GAM to a univariate or multivariate set of discrete time series — mvgam","text":"Nicholas J Clark","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Fit a Bayesian dynamic GAM to a univariate or multivariate set of discrete time series — mvgam","text":"","code":"if (FALSE) { # Simulate a collection of three time series that have shared seasonal dynamics dat <- sim_mvgam(T = 80, n_series = 3, prop_missing = 0.1, trend_rel = 0.6) # Plot key summary statistics for a single series plot_mvgam_series(data = dat$data_train, series = 1) # Plot all series together plot_mvgam_series(data = dat$data_train, series = 'all') # Formulate a model using Stan where series share a cyclic smooth for # seasonality and each series has an independent random walk temporal process; # Set run_model = FALSE to inspect the returned objects mod1 <- mvgam(formula = y ~ s(season, bs = 'cc'), data = dat$data_train, trend_model = 'RW', family = 'poisson', use_stan = TRUE, run_model = FALSE) # View the model code in Stan language code(mod1) # Inspect the data objects needed to condition the model str(mod1$model_data) # Inspect the initial value function used to initialise the MCMC chains mod1$inits # The following code can be used to run the model outside of mvgam; first using rstan model_data <- mod1$model_data library(rstan) fit <- stan(model_code = mod1$model_file, data = model_data, init = mod1$inits) # Now using cmdstanr library(cmdstanr) model_data <- mod1$model_data cmd_mod <- cmdstan_model(write_stan_file(mod1$model_file), stanc_options = list('canonicalize=deprecations,braces,parentheses')) cmd_mod$print() fit <- cmd_mod$sample(data = model_data, chains = 4, parallel_chains = 4, refresh = 100, init = mod1$inits) # Now fit the model using mvgam with the Stan backend mod1 <- mvgam(formula = y ~ s(season, bs = 'cc'), data = dat$data_train, trend_model = 'RW', family = poisson(), use_stan = TRUE) # Extract the model summary summary(mod1) # Plot the estimated historical trend and forecast for one series plot(mod1, type = 'trend', series = 1) plot(mod1, type = 'forecast', series = 1) # Compute the forecast using covariate information in data_test plot(object = mod1, type = 'trend', newdata = dat$data_test, series = 1) plot(object = mod1, type = 'forecast', newdata = dat$data_test, series = 1) # Plot the estimated seasonal smooth function plot(mod1, type = 'smooths') # Plot estimated first derivatives of the smooth plot(mod1, type = 'smooths', derivatives = TRUE) # Plot partial residuals of the smooth plot(mod1, type = 'smooths', residuals = TRUE) # Plot posterior realisations for the smooth plot(mod1, type = 'smooths', realisations = TRUE) # Extract observation model beta coefficient draws as a data.frame beta_draws_df <- as.data.frame(mod1, variable = 'betas') head(beta_draws_df) str(beta_draws_df) # Example of supplying a trend_map so that some series can share # latent trend processes sim <- sim_mvgam(n_series = 3) mod_data <- sim$data_train # Here, we specify only two latent trends; series 1 and 2 share a trend, # while series 3 has it's own unique latent trend trend_map <- data.frame(series = unique(mod_data$series), trend = c(1,1,2)) # Fit the model using AR1 trends mod1 <- mvgam(y ~ s(season, bs = 'cc'), trend_map = trend_map, trend_model = 'AR1', data = mod_data, return_model_data = TRUE) # The mapping matrix is now supplied as data to the model in the 'Z' element mod1$model_data$Z code(mod1) # The first two series share an identical latent trend; the third is different plot(mod1, type = 'trend', series = 1) plot(mod1, type = 'trend', series = 2) plot(mod1, type = 'trend', series = 3) # Example of how to use dynamic coefficients # Simulate a time-varying coefficient for the effect of temperature set.seed(3) N = 200 beta_temp <- vector(length = N) beta_temp[1] <- 0.4 for(i in 2:N){ beta_temp[i] <- rnorm(1, mean = beta_temp[i - 1], sd = 0.025) } # Simulate the temperature covariate temp <- rnorm(N, sd = 1) # Simulate the Gaussian observation process out <- rnorm(N, mean = 4 + beta_temp * temp, sd = 0.5) # Gather necessary data into a data.frame; split into training / testing data = data.frame(out, temp, time = seq_along(temp)) data_train <- data[1:180,] data_test <- data[181:200,] # Fit the model using the dynamic() formula helper mod <- mvgam(formula = out ~ dynamic(temp, rho = 8), family = gaussian(), data = data_train, newdata = data_test) # Inspect the model summary, forecast and time-varying coefficient distribution summary(mod) plot(mod, type = 'smooths') plot(mod, type = 'forecast', newdata = data_test) # Propagating the smooth term shows how the coefficient is expected to evolve plot_mvgam_smooth(mod, smooth = 1, newdata = data) abline(v = 180, lty = 'dashed', lwd = 2) # Example showing how to incorporate an offset; simulate some count data # with different means per series set.seed(100) dat <- sim_mvgam(trend_rel = 0, mu = c(0, 2, 2), seasonality = 'hierarchical') # Add offset terms to the training and testing data dat$data_train$offset <- 0.5 * as.numeric(dat$data_train$series) dat$data_test$offset <- 0.5 * as.numeric(dat$data_test$series) # Fit a model that includes the offset in the linear predictor as well as # hierarchical seasonal smooths mod1 <- mvgam(formula = y ~ offset(offset) + s(series, bs = 're') + s(season, bs = 'cc') + s(season, by = series, m = 1, k = 5), data = dat$data_train, trend_model = 'None', use_stan = TRUE) # Inspect the model file to see the modification to the linear predictor # (eta) mod1$model_file # Forecasts for the first two series will differ in magnitude layout(matrix(1:2, ncol = 2)) plot(mod1, type = 'forecast', series = 1, newdata = dat$data_test, ylim = c(0, 75)) plot(mod1, type = 'forecast', series = 2, newdata = dat$data_test, ylim = c(0, 75)) layout(1) # Changing the offset for the testing data should lead to changes in # the forecast dat$data_test$offset <- dat$data_test$offset - 2 plot(mod1, 'forecast', newdata = dat$data_test) # Relative Risks can be computed by fixing the offset to the same value # for each series dat$data_test$offset <- rep(1, NROW(dat$data_test)) preds_rr <- predict(mod1, type = 'link', newdata = dat$data_test) series1_inds <- which(dat$data_test$series == 'series_1') series2_inds <- which(dat$data_test$series == 'series_2') # Relative Risks are now more comparable among series layout(matrix(1:2, ncol = 2)) plot(preds_rr[1, series1_inds], type = 'l', col = 'grey75', ylim = range(preds_rr), ylab = 'Series1 Relative Risk', xlab = 'Time') for(i in 2:50){ lines(preds_rr[i, series1_inds], col = 'grey75') } plot(preds_rr[1, series2_inds], type = 'l', col = 'darkred', ylim = range(preds_rr), ylab = 'Series2 Relative Risk', xlab = 'Time') for(i in 2:50){ lines(preds_rr[i, series2_inds], col = 'darkred') } layout(1) }"},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_draws.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract posterior draws from fitted mvgam objects — mvgam_draws","title":"Extract posterior draws from fitted mvgam objects — mvgam_draws","text":"Extract posterior draws conventional formats data.frames, matrices, arrays.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_draws.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract posterior draws from fitted mvgam objects — mvgam_draws","text":"","code":"# S3 method for mvgam as.data.frame( x, row.names = NULL, optional = TRUE, variable = \"betas\", regex = FALSE, ... ) # S3 method for mvgam as.matrix(x, variable = \"betas\", regex = FALSE, ...)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_draws.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract posterior draws from fitted mvgam objects — mvgam_draws","text":"x list object class mvgam row.names Ignored optional Ignored variable character specifying parameters extract. Can either one following options: obs_params (parameters specific observation model, overdispsersions negative binomial models observation error SD gaussian / student-t models) betas (beta coefficients GAM observation model linear predictor; default) smooth_params (smoothing parameters GAM observation model) linpreds (estimated linear predictors whatever link scale used model) trend_params (parameters governing trend dynamics, AR parameters, trend SD parameters Gaussian Process parameters) trend_betas (beta coefficients GAM latent process model linear predictor; available trend_formula supplied original model) trend_smooth_params (process model GAM smoothing parameters; available trend_formula supplied original model) trend_linpreds (process model linear predictors identity scale; available trend_formula supplied original model) can character vector providing variables extract regex Logical. using one prespecified options extractions, variable treated (vector ) regular expressions? variable x matching least one regular expressions selected. Defaults FALSE. ... Ignored","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_draws.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extract posterior draws from fitted mvgam objects — mvgam_draws","text":"data.frame, matrix, array containing posterior draws.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_draws.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Extract posterior draws from fitted mvgam objects — mvgam_draws","text":"","code":"if (FALSE) { sim <- sim_mvgam(family = Gamma()) mod1 <- mvgam(y ~ s(season, bs = 'cc'), trend_model = 'AR1', data = sim$data_train, family = Gamma()) beta_draws_df <- as.data.frame(mod1, variable = 'betas') head(beta_draws_df) str(beta_draws_df) beta_draws_mat <- as.data.frame(mod1, variable = 'betas') head(beta_draws_mat) str(beta_draws_mat)}"},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_families.html","id":null,"dir":"Reference","previous_headings":"","what":"Supported mvgam families — mvgam_families","title":"Supported mvgam families — mvgam_families","text":"Supported mvgam families","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_families.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Supported mvgam families — mvgam_families","text":"","code":"tweedie(link = \"log\") student_t(link = \"identity\")"},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_families.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Supported mvgam families — mvgam_families","text":"link specification family link function. present changed","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_families.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Supported mvgam families — mvgam_families","text":"mvgam currently supports following standard observation families: gaussian real-valued data poisson count data Gamma non-negative real-valued data addition, following extended families mgcv package supported: betar proportional data (0,1) nb count data Finally, mvgam supports three extended families described : lognormal non-negative real-valued data tweedie count data (power parameter p fixed 1.5) student-t real-valued data Note poisson(), nb(), tweedie() available using JAGS. families, apart tweedie(), supported using Stan.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_families.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Supported mvgam families — mvgam_families","text":"Nicholas J Clark","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_forecast-class.html","id":null,"dir":"Reference","previous_headings":"","what":"mvgam_forecast object description — mvgam_forecast-class","title":"mvgam_forecast object description — mvgam_forecast-class","text":"mvgam_forecast object returned function hindcast forecast. Run methods(class = \"mvgam_forecast\") see overview available methods.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_forecast-class.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"mvgam_forecast object description — mvgam_forecast-class","text":"mvgam_forecast object contains following elements: call original observation model formula trend_call trend_formula supplied, original trend model formula returned. Otherwise NULL family character description observation distribution trend_model character description latent trend model drift Logical specifying whether drift term used trend model use_lv Logical flag indicating whether latent dynamic factors used model fit_engine Character describing fit engine, either stan jags type type predictions included (either link, response trend) series_names Names time series, taken levels(data$series) original model fit train_observations list training observation vectors length n_series test_observations forecast function used, list test observation vectors length n_series. Otherwise NULL hindcasts list posterior hindcast distributions length n_series. forecasts forecast function used, list posterior forecast distributions length n_series. Otherwise NULL","code":""},{"path":[]},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_forecast-class.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"mvgam_forecast object description — mvgam_forecast-class","text":"Nicholas J Clark","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_trends.html","id":null,"dir":"Reference","previous_headings":"","what":"Supported mvgam trend models — mvgam_trends","title":"Supported mvgam trend models — mvgam_trends","text":"Supported mvgam trend models","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_trends.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Supported mvgam trend models — mvgam_trends","text":"mvgam currently supports following dynamic trend models: RW Random Walk AR1 Autoregressive model AR coefficient lag 1 AR2 Autoregressive model AR coefficients lags 1 2 AR3 Autoregressive model AR coefficients lags 1, 2 3 VAR1 Vector Autoregressive model VAR coefficients lag 1; contemporaneously uncorrelated process errors VAR1cor Vector Autoregressive model VAR coefficients lag 1; contemporaneously correlated process errors GP Squared exponential Gaussian Process None latent trend fitted Dynamic factor models can used latent factors evolve either RW, AR1, AR2, AR3 GP. Note RW, AR1, AR2 AR3 available using JAGS. trend models supported using Stan. multivariate trend models (.e. VAR VARcor models), users can either fix trend error covariances 0 (using VAR) estimate potentially allow contemporaneously correlated errors using VARcor. VAR models, stationarity latent process enforced prior using parameterisation given Heaps (2022). Stationarity enforced using AR1, AR2 AR3 models, though can changed user specifying lower upper bounds autoregressive parameters using functionality get_mvgam_priors priors argument mvgam","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_trends.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Supported mvgam trend models — mvgam_trends","text":"Sarah E. Heaps (2022) Enforcing stationarity prior Vector Autoregressions. Journal Computational Graphical Statistics. 32:1, 1-10.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/pfilter_mvgam_fc.html","id":null,"dir":"Reference","previous_headings":"","what":"Forecast from a particle filtered mvgam object — pfilter_mvgam_fc","title":"Forecast from a particle filtered mvgam object — pfilter_mvgam_fc","text":"function generates forecast set particles capture unique proposal current state system modelled mvgam object. covariate timepoint information data_test used generate GAM component forecast, trends run forward time according state space dynamics. forecast weighted ensemble, weights determined particle's proposal likelihood prior recent assimilation step","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/pfilter_mvgam_fc.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Forecast from a particle filtered mvgam object — pfilter_mvgam_fc","text":"","code":"pfilter_mvgam_fc( file_path = \"pfilter\", n_cores = 2, newdata, data_test, plot_legend = TRUE, legend_position = \"topleft\", ylim, return_forecasts = FALSE )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/pfilter_mvgam_fc.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Forecast from a particle filtered mvgam object — pfilter_mvgam_fc","text":"file_path character string specifying file path particles saved n_cores integer specifying number cores generating particle forecasts parallel newdata dataframe list test data containing least 'series' time', addition variables included linear predictor formula data_test Deprecated. Still works place newdata users recommended use newdata instead seamless integration R workflows plot_legend logical stating whether include legend highlight observations used calibration assimilated particle filter legend_position legend location may specified setting x single keyword list \"bottomright\", \"bottom\", \"bottomleft\", \"left\", \"topleft\", \"top\", \"topright\", \"right\" \"center\". places legend inside plot frame given location. ylim Optional vector y-axis limits (min, max). limits used plots return_forecasts logical. TRUE, returned list object contain plots forecasts well forecast objects (matrix dimension n_particles x horizon)","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/pfilter_mvgam_fc.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Forecast from a particle filtered mvgam object — pfilter_mvgam_fc","text":"named list containing functions call base R plots series' forecast. Optionally actual forecasts returned within list separate list matrices","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/pfilter_mvgam_init.html","id":null,"dir":"Reference","previous_headings":"","what":"Initiate particles for online filtering from a fitted mvgam object — pfilter_mvgam_init","title":"Initiate particles for online filtering from a fitted mvgam object — pfilter_mvgam_init","text":"function generates set particles captures unique proposal current state system. next observation data_assim assimilated particles weighted proposal's multivariate composite likelihood update model's forecast distribution","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/pfilter_mvgam_init.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Initiate particles for online filtering from a fitted mvgam object — pfilter_mvgam_init","text":"","code":"pfilter_mvgam_init( object, newdata, data_assim, n_particles = 1000, file_path = \"pfilter\", n_cores = 2 )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/pfilter_mvgam_init.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Initiate particles for online filtering from a fitted mvgam object — pfilter_mvgam_init","text":"object list object returned mvgam newdata dataframe list test data containing least one observation per series (beyond last observation seen model object) assimilated particle filter. least contain 'series' 'time' one-step ahead horizon, addition variables included linear predictor object data_assim Deprecated. Still works place newdata users recommended use newdata instead seamless integration R workflows n_particles integer specifying number unique particles generate tracking latent system state file_path character string specifying file path saving initiated particles n_cores integer specifying number cores generating particle forecasts parallel","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/pfilter_mvgam_init.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Initiate particles for online filtering from a fitted mvgam object — pfilter_mvgam_init","text":"list object length = n_particles containing information parameters current state estimates particle generated saved, along important information original model, .rda object file_path","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/pfilter_mvgam_online.html","id":null,"dir":"Reference","previous_headings":"","what":"Automatic online particle filtering for assimilating new observations into a fitted mvgam model — pfilter_mvgam_online","title":"Automatic online particle filtering for assimilating new observations into a fitted mvgam model — pfilter_mvgam_online","text":"function operates sequentially new observations data_assim update posterior forecast distribution. wrapper calls pfilter_mvgam_smooth. iteration, next observation assimilated particles weighted proposal's multivariate composite likelihood","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/pfilter_mvgam_online.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Automatic online particle filtering for assimilating new observations into a fitted mvgam model — pfilter_mvgam_online","text":"","code":"pfilter_mvgam_online( newdata, data_assim, file_path = \"pfilter\", threshold = 0.5, use_resampling = FALSE, kernel_lambda = 0.25, n_cores = 1 )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/pfilter_mvgam_online.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Automatic online particle filtering for assimilating new observations into a fitted mvgam model — pfilter_mvgam_online","text":"newdata dataframe list test data containing least one observation per series (beyond last observation seen model initialising particles pfilter_mvgam_init previous calls pfilter_mvgam_online. least contain 'series' 'time' one-step ahead horizon, addition variables included linear predictor object data_assim Deprecated. Still works place newdata users recommended use newdata instead seamless integration R workflows file_path character string specifying file path locating particles threshold proportional numeric specifying Effective Sample Size limit resampling particles triggered (calculated ESS / n_particles) use_resampling == TRUE. 0 1 use_resampling logical specifying whether resampling used ESS falls specified threshold. Default option FALSE, relying instead kernel smoothing maintain particle diversity kernel_lambda proportional numeric specifying strength kernel smoothing use pulling low weight particles toward high likelihood state space. 0 1 n_cores integer specifying number cores generating particle forecasts parallel","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/pfilter_mvgam_online.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Automatic online particle filtering for assimilating new observations into a fitted mvgam model — pfilter_mvgam_online","text":"list object length = n_particles containing information parameters current state estimates particle generated saved, along important information original model, .rda object file_path","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/pfilter_mvgam_smooth.html","id":null,"dir":"Reference","previous_headings":"","what":"Assimilate new observations into a fitted mvgam model using resampling and kernel smoothing — pfilter_mvgam_smooth","title":"Assimilate new observations into a fitted mvgam model using resampling and kernel smoothing — pfilter_mvgam_smooth","text":"function operates new observation next_assim update posterior forecast distribution. next observation assimilated particle weights updated light recent multivariate composite likelihood. Low weight particles smoothed towards high weight state space using importance sampling, options given using resampling high weight particles Effective Sample Size falls user-specified threshold","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/pfilter_mvgam_smooth.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Assimilate new observations into a fitted mvgam model using resampling and kernel smoothing — pfilter_mvgam_smooth","text":"","code":"pfilter_mvgam_smooth( particles, mgcv_model, next_assim, threshold = 0.25, n_cores = 1, use_resampling = FALSE, kernel_lambda = 0.5 )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/pfilter_mvgam_smooth.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Assimilate new observations into a fitted mvgam model using resampling and kernel smoothing — pfilter_mvgam_smooth","text":"particles list particles run one observation prior observation next_assim mgcv_model gam model returned call link{mvgam} next_assim dataframe test data containing one observation per series (beyond last observation seen model initialising particles pfilter_mvgam_init previous calls pfilter_mvgam_online. least contain 'series' 'time' one-step ahead horizon, addition variables included linear predictor object threshold proportional numeric specifying Effective Sample Size limit resampling particles triggered (calculated ESS / n_particles) use_resampling == TRUE. 0 1 n_cores integer specifying number cores generating particle forecasts parallel use_resampling logical specifying whether resampling used ESS falls specified threshold. Note resampling can result loss original model's diversity GAM beta coefficients, may undesirable consequences forecast distribution. use_resampling TRUE, effort made remedy assigning randomly sampled draws GAM beta coefficients original model's distribution particle. however guarantee loss diversity, especially successive resampling take place. Default option therefore FALSE kernel_lambda proportional numeric specifying strength smoothing use pulling low weight particles toward high likelihood state space. 0 1","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/pfilter_mvgam_smooth.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Assimilate new observations into a fitted mvgam model using resampling and kernel smoothing — pfilter_mvgam_smooth","text":"list object length = n_particles containing information parameters current state estimates particle","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/pipe.html","id":null,"dir":"Reference","previous_headings":"","what":"Pipe operator — %>%","title":"Pipe operator — %>%","text":"See magrittr::%>% details.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/pipe.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Pipe operator — %>%","text":"","code":"lhs %>% rhs"},{"path":"https://nicholasjclark.github.io/mvgam/reference/pipe.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Pipe operator — %>%","text":"lhs value magrittr placeholder. rhs function call using magrittr semantics.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/pipe.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Pipe operator — %>%","text":"result calling rhs(lhs).","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot.mvgam.html","id":null,"dir":"Reference","previous_headings":"","what":"Default mvgam plots — plot.mvgam","title":"Default mvgam plots — plot.mvgam","text":"function takes fitted mvgam object produces plots smooth functions, forecasts, trends uncertainty components","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot.mvgam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Default mvgam plots — plot.mvgam","text":"","code":"# S3 method for mvgam plot( x, type = \"residuals\", series = 1, residuals = FALSE, newdata, data_test, trend_effects = FALSE, ... )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot.mvgam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Default mvgam plots — plot.mvgam","text":"x list object returned mvgam. See mvgam() type character specifying type plot return. Options : 'series, residuals, smooths, re (random effect smooths), pterms (parametric effects), forecast, trend, uncertainty, factors series integer specifying series set plotted. ignored type == 're' residuals logical. TRUE type = residuals, posterior quantiles partial residuals added plots 1-D smooths series ribbon rectangles. Partial residuals smooth term median Dunn-Smyth residuals obtained dropping term concerned model, leaving estimates fixed (.e. estimates term plus original median Dunn-Smyth residuals). Note mvgam works Dunn-Smyth residuals working residuals, used mgcv, magnitudes partial residuals different expect plot.gam. Interpretation similar though, partial residuals evenly scattered around smooth function function well estimated newdata Optional dataframe list test data containing least 'series' 'time' addition variables included linear predictor original formula. argument optional plotting sample forecast period observations (type = forecast) required plotting uncertainty components (type = uncertainty). data_test Deprecated. Still works place newdata users recommended use newdata instead seamless integration R workflows trend_effects logical. TRUE trend_formula used model fitting, terms trend (.e. process) model plotted ... Additional arguments individual plotting function.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot.mvgam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Default mvgam plots — plot.mvgam","text":"base R plot set plots","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot.mvgam.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Default mvgam plots — plot.mvgam","text":"plots useful getting overview fitted model estimated random effects smooth functions, individual plotting functions generally offer customisation.","code":""},{"path":[]},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot.mvgam.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Default mvgam plots — plot.mvgam","text":"Nicholas J Clark","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot.mvgam_lfo.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot Pareto-k and ELPD values from a leave-future-out object — plot.mvgam_lfo","title":"Plot Pareto-k and ELPD values from a leave-future-out object — plot.mvgam_lfo","text":"function takes object class mvgam_lfo create several informative diagnostic plots","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot.mvgam_lfo.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot Pareto-k and ELPD values from a leave-future-out object — plot.mvgam_lfo","text":"","code":"# S3 method for mvgam_lfo plot(x, ...)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot.mvgam_lfo.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot Pareto-k and ELPD values from a leave-future-out object — plot.mvgam_lfo","text":"x object class mvgam_lfo ... Ignored","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot.mvgam_lfo.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot Pareto-k and ELPD values from a leave-future-out object — plot.mvgam_lfo","text":"base R plot Pareto-k ELPD values evaluation timepoints. Pareto-k plot, dashed red line indicates specified threshold chosen triggering model refits. ELPD plot, dashed red line indicated bottom 10% quantile ELPD values. Points threshold may represent outliers difficult forecast","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_factors.html","id":null,"dir":"Reference","previous_headings":"","what":"Latent factor summaries for a fitted mvgam object — plot_mvgam_factors","title":"Latent factor summaries for a fitted mvgam object — plot_mvgam_factors","text":"function takes fitted mvgam object returns plots summary statistics latent dynamic factors","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_factors.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Latent factor summaries for a fitted mvgam object — plot_mvgam_factors","text":"","code":"plot_mvgam_factors(object, plot = TRUE)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_factors.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Latent factor summaries for a fitted mvgam object — plot_mvgam_factors","text":"object list object returned mvgam plot logical specifying whether factors plotted","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_factors.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Latent factor summaries for a fitted mvgam object — plot_mvgam_factors","text":"dataframe factor contributions , optionally, series base R plots","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_factors.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Latent factor summaries for a fitted mvgam object — plot_mvgam_factors","text":"model object estimated using dynamic factors, possible factors contributed estimated trends. due regularisation penalty acts independently factor's Gaussian precision, squeeze un-needed factors white noise process (effectively dropping factor model). function, factor tested null hypothesis white noise calculating sum factor's 2nd derivatives. factor larger contribution larger sum due weaker penalty factor's precision. plot == TRUE, factors also plotted.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_factors.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Latent factor summaries for a fitted mvgam object — plot_mvgam_factors","text":"Nicholas J Clark","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_forecasts.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot mvgam posterior predictions for a specified series — plot_mvgam_forecasts","title":"Plot mvgam posterior predictions for a specified series — plot_mvgam_forecasts","text":"Plot mvgam posterior predictions specified series","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_forecasts.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot mvgam posterior predictions for a specified series — plot_mvgam_forecasts","text":"","code":"plot_mvgam_fc( object, series = 1, newdata, data_test, realisations = FALSE, n_realisations = 15, hide_xlabels = FALSE, xlab, ylab, ylim, n_cores = 1, return_forecasts = FALSE, return_score = FALSE, ... ) # S3 method for mvgam_forecast plot( x, series = 1, realisations = FALSE, n_realisations = 15, hide_xlabels = FALSE, xlab, ylab, ylim, return_score = FALSE, ... )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_forecasts.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot mvgam posterior predictions for a specified series — plot_mvgam_forecasts","text":"object list object returned mvgam series integer specifying series set plotted newdata Optional dataframe list test data containing least 'series' 'time' addition variables included linear predictor original formula. included, covariate information newdata used generate forecasts fitted model equations. newdata originally included call mvgam, forecasts already produced generative model simply extracted plotted. However newdata supplied original model call, assumption made newdata supplied comes sequentially data supplied data original model (.e. assume time gap last observation series 1 data first observation series 1 newdata). newdata contains observations column y, observations used compute Discrete Rank Probability Score forecast distribution data_test Deprecated. Still works place newdata users recommended use newdata instead seamless integration R workflows realisations logical. TRUE, forecast realisations shown spaghetti plot, making easier visualise diversity possible forecasts. FALSE, default, empirical quantiles forecast distribution shown n_realisations integer specifying number posterior realisations plot, realisations = TRUE. Ignored otherwise hide_xlabels logical. TRUE, xlabels printed allow user add custom labels using axis base R xlab label x axis. ylab label y axis. ylim Optional vector y-axis limits (min, max) n_cores integer specifying number cores generating forecasts parallel return_forecasts logical. TRUE, function plot forecast well returning forecast object (matrix dimension n_samples x horizon) return_score logical. TRUE sample test data provided newdata, probabilistic score calculated returned. score used depend observation family fitted model. Discrete families (poisson, negative binomial, tweedie) use Discrete Rank Probability Score. families use Continuous Rank Probability Score. value returned sum scores within sample forecast horizon ... par graphical parameters. x Object class mvgam_forecast","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_forecasts.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot mvgam posterior predictions for a specified series — plot_mvgam_forecasts","text":"base R graphics plot optional list containing forecast distribution sample probabilistic forecast score","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_forecasts.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot mvgam posterior predictions for a specified series — plot_mvgam_forecasts","text":"plot_mvgam_fc draws posterior predictions object class mvgam calculates posterior empirical quantiles. plot.mvgam_forecast takes object class mvgam_forecast, forecasts already computed, plots resulting forecast distribution. realisations = FALSE, posterior quantiles plotted along true observed data used train model. Otherwise, spaghetti plot returned show possible forecast paths.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_pterms.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot mvgam parametric term partial effects — plot_mvgam_pterms","title":"Plot mvgam parametric term partial effects — plot_mvgam_pterms","text":"function plots posterior empirical quantiles partial effects parametric terms","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_pterms.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot mvgam parametric term partial effects — plot_mvgam_pterms","text":"","code":"plot_mvgam_pterms(object, trend_effects = FALSE)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_pterms.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot mvgam parametric term partial effects — plot_mvgam_pterms","text":"object list object returned mvgam trend_effects logical. TRUE trend_formula used model fitting, terms trend (.e. process) model plotted","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_pterms.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot mvgam parametric term partial effects — plot_mvgam_pterms","text":"base R graphics plot","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_pterms.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot mvgam parametric term partial effects — plot_mvgam_pterms","text":"Posterior empirical quantiles parametric term's partial effect estimates (link scale) calculated visualised ribbon plots. effects can interpreted partial effect parametric term contributes terms model set 0","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_randomeffects.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot mvgam random effect terms — plot_mvgam_randomeffects","title":"Plot mvgam random effect terms — plot_mvgam_randomeffects","text":"function plots posterior empirical quantiles random effect smooths (bs = re)","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_randomeffects.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot mvgam random effect terms — plot_mvgam_randomeffects","text":"","code":"plot_mvgam_randomeffects(object, trend_effects = FALSE)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_randomeffects.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot mvgam random effect terms — plot_mvgam_randomeffects","text":"object list object returned mvgam trend_effects logical. TRUE trend_formula used model fitting, terms trend (.e. process) model plotted","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_randomeffects.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot mvgam random effect terms — plot_mvgam_randomeffects","text":"base R graphics plot","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_randomeffects.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot mvgam random effect terms — plot_mvgam_randomeffects","text":"Posterior empirical quantiles random effect coefficient estimates (link scale) calculated visualised ribbon plots. Labels coefficients taken levels original factor variable used specify smooth model's formula","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_resids.html","id":null,"dir":"Reference","previous_headings":"","what":"Residual diagnostics for a fitted mvgam object — plot_mvgam_resids","title":"Residual diagnostics for a fitted mvgam object — plot_mvgam_resids","text":"function takes fitted mvgam object returns various residual diagnostic plots","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_resids.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Residual diagnostics for a fitted mvgam object — plot_mvgam_resids","text":"","code":"plot_mvgam_resids(object, series = 1, n_bins = 15, newdata, data_test)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_resids.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Residual diagnostics for a fitted mvgam object — plot_mvgam_resids","text":"object list object returned mvgam series integer specifying series set plotted n_bins integer specifying number bins use binning fitted values newdata Optional dataframe list test data containing least 'series', 'y', 'time' addition variables included linear predictor formula. included, covariate information newdata used generate forecasts fitted model equations. newdata originally included call mvgam, forecasts already produced generative model simply extracted used calculate residuals. However newdata supplied original model call, assumption made newdata supplied comes sequentially data supplied data original model (.e. assume time gap last observation series 1 data_train first observation series 1 newdata). data_test Deprecated. Still works place newdata users recommended use newdata instead seamless integration R workflows","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_resids.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Residual diagnostics for a fitted mvgam object — plot_mvgam_resids","text":"series base R plots","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_resids.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Residual diagnostics for a fitted mvgam object — plot_mvgam_resids","text":"total four base R plots generated examine Dunn-Smyth residuals specified series. Plots include residuals vs fitted values plot, Q-Q plot, two plots check remaining temporal autocorrelation residuals. Note, plots use posterior medians fitted values / residuals, uncertainty represented.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_resids.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Residual diagnostics for a fitted mvgam object — plot_mvgam_resids","text":"Nicholas J Clark","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_series.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot observed time series used for mvgam modelling — plot_mvgam_series","title":"Plot observed time series used for mvgam modelling — plot_mvgam_series","text":"function takes either fitted mvgam object data_train object produces plots observed time series, ACF, CDF histograms exploratory data analysis","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_series.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot observed time series used for mvgam modelling — plot_mvgam_series","text":"","code":"plot_mvgam_series( object, data, data_train, newdata, data_test, y = \"y\", lines = TRUE, series = 1, n_bins, log_scale = FALSE )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_series.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot observed time series used for mvgam modelling — plot_mvgam_series","text":"object Optional list object returned mvgam. Either object data_train must supplied. data Optional dataframe list training data containing least 'series' 'time'. Use argument training data gathered correct format mvgam modelling model yet fitted. data_train Deprecated. Still works place data users recommended use data instead seamless integration R workflows newdata Optional dataframe list test data containing least 'series' 'time' forecast horizon, addition variables included linear predictor formula. included, observed values test data compared model's forecast distribution exploring biases model predictions. data_test Deprecated. Still works place newdata users recommended use newdata instead seamless integration R workflows y Character. name outcome variable supplied data? Defaults 'y' lines Logical. TRUE, line plots used visualising time series. FALSE, points used. series Either integer specifying series set plotted string '', plots series available supplied data n_bins integer specifying number bins use binning observed values plotting histogram. Default use number bins returned call hist base R log_scale logical. series == '', flag used control whether time series plot shown log scale (using log(Y + 1)). can useful visualising many series may different observed ranges. Default FALSE","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_series.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot observed time series used for mvgam modelling — plot_mvgam_series","text":"set base R graphics plots. series integer, plots show observed time series, autocorrelation cumulative distribution functions, histogram series. series == '', set observed time series plots returned series shown plot single focal series highlighted, remaining series shown faint gray lines.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_series.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Plot observed time series used for mvgam modelling — plot_mvgam_series","text":"Nicholas J Clark","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_smooth.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot mvgam smooth terms — plot_mvgam_smooth","title":"Plot mvgam smooth terms — plot_mvgam_smooth","text":"function plots posterior empirical quantiles series-specific smooth term","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_smooth.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot mvgam smooth terms — plot_mvgam_smooth","text":"","code":"plot_mvgam_smooth( object, trend_effects = FALSE, series = 1, smooth, residuals = FALSE, n_resid_bins = 25, realisations = FALSE, n_realisations = 15, derivatives = FALSE, newdata )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_smooth.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot mvgam smooth terms — plot_mvgam_smooth","text":"object list object returned mvgam trend_effects logical. TRUE trend_formula used model fitting, terms trend (.e. process) model plotted series integer specifying series set plotted smooth either character integer specifying smooth term plotted residuals logical. TRUE posterior quantiles partial residuals added plots 1-D smooths series ribbon rectangles. Partial residuals smooth term median Dunn-Smyth residuals obtained dropping term concerned model, leaving estimates fixed (.e. estimates term plus original median Dunn-Smyth residuals). Note mvgam works Dunn-Smyth residuals working residuals, used mgcv, magnitudes partial residuals different expect plot.gam. Interpretation similar though, partial residuals evenly scattered around smooth function function well estimated n_resid_bins integer specifying number bins group covariate plotting partial residuals. Setting argument high can make messy plots difficult interpret, setting low likely mask potentially useful patterns partial residuals. Default 25 realisations logical. TRUE, posterior realisations shown spaghetti plot, making easier visualise diversity possible functions. FALSE, default, empirical quantiles posterior distribution shown n_realisations integer specifying number posterior realisations plot, realisations = TRUE. Ignored otherwise derivatives logical. TRUE, additional plot returned show estimated 1st derivative specified smooth (Note, works univariate smooths) newdata Optional dataframe predicting smooth, containing least 'series' addition variables included linear predictor original model's formula. Note currently supported plotting univariate smooths","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_smooth.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot mvgam smooth terms — plot_mvgam_smooth","text":"base R graphics plot","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_smooth.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot mvgam smooth terms — plot_mvgam_smooth","text":"Smooth functions shown empirical quantiles (spaghetti plots) posterior partial expectations across sequence 500 values variable's min max, zeroing effects variables. present, univariate bivariate smooth plots allowed, though note bivariate smooths rely default behaviour plot.gam. nuanced visualisation, supply newdata just predicting gam model","code":""},{"path":[]},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_trend.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot mvgam latent trend for a specified series — plot_mvgam_trend","title":"Plot mvgam latent trend for a specified series — plot_mvgam_trend","text":"Plot mvgam latent trend specified series","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_trend.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot mvgam latent trend for a specified series — plot_mvgam_trend","text":"","code":"plot_mvgam_trend( object, series = 1, newdata, data_test, realisations = FALSE, n_realisations = 15, n_cores = 1, derivatives = FALSE, hide_xlabels = FALSE, xlab, ylab, ... )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_trend.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot mvgam latent trend for a specified series — plot_mvgam_trend","text":"object list object returned mvgam series integer specifying series set plotted newdata Optional dataframe list test data containing least 'series' 'time' addition variables included linear predictor original formula. data_test Deprecated. Still works place newdata users recommended use newdata instead seamless integration R workflows realisations logical. TRUE, posterior trend realisations shown spaghetti plot, making easier visualise diversity possible trend paths. FALSE, default, empirical quantiles posterior distribution shown n_realisations integer specifying number posterior realisations plot, realisations = TRUE. Ignored otherwise n_cores integer specifying number cores generating trend forecasts parallel derivatives logical. TRUE, additional plot returned show estimated 1st derivative estimated trend hide_xlabels logical. TRUE, xlabels printed allow user add custom labels using axis base R. Ignored derivatives = TRUE xlab label x axis. ylab label y axis. ... par graphical parameters.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_uncertainty.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot mvgam forecast uncertainty contributions for a specified series — plot_mvgam_uncertainty","title":"Plot mvgam forecast uncertainty contributions for a specified series — plot_mvgam_uncertainty","text":"Plot mvgam forecast uncertainty contributions specified series","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_uncertainty.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot mvgam forecast uncertainty contributions for a specified series — plot_mvgam_uncertainty","text":"","code":"plot_mvgam_uncertainty( object, series = 1, newdata, data_test, legend_position = \"topleft\", hide_xlabels = FALSE )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_uncertainty.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot mvgam forecast uncertainty contributions for a specified series — plot_mvgam_uncertainty","text":"object list object returned mvgam series integer specifying series set plotted newdata dataframe list containing least 'series' 'time' forecast horizon, addition variables included linear predictor formula data_test Deprecated. Still works place newdata users recommended use newdata instead seamless integration R workflows legend_position location may also specified setting x single keyword list: \"none\", \"bottomright\", \"bottom\", \"bottomleft\", \"left\", \"topleft\", \"top\", \"topright\", \"right\" \"center\". places legend inside plot frame given location (\"none\"). hide_xlabels logical. TRUE, xlabels printed allow user add custom labels using axis base R","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/portal_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Portal Project rodent capture survey data — portal_data","title":"Portal Project rodent capture survey data — portal_data","text":"dataset containing timeseries select rodent species captures control plots Portal Project","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/portal_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Portal Project rodent capture survey data — portal_data","text":"","code":"portal_data"},{"path":"https://nicholasjclark.github.io/mvgam/reference/portal_data.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Portal Project rodent capture survey data — portal_data","text":"dataframe containing following fields: moon time sampling lunar cycles DM Total captures species DM Total captures species DM Total captures species PP DM Total captures species OT year Sampling year month Sampling month mintemp Monthly mean minimum temperature precipitation Monthly mean precipitation ndvi Monthly mean Normalised Difference Vegetation Index","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/portal_data.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Portal Project rodent capture survey data — portal_data","text":"https://www.weecology.org/data-projects/portal/","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/ppc.mvgam.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot mvgam posterior predictive checks for a specified series — ppc.mvgam","title":"Plot mvgam posterior predictive checks for a specified series — ppc.mvgam","text":"Plot mvgam posterior predictive checks specified series","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/ppc.mvgam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot mvgam posterior predictive checks for a specified series — ppc.mvgam","text":"","code":"ppc(object, ...) # S3 method for mvgam ppc( object, newdata, data_test, series = 1, type = \"hist\", n_bins, legend_position, xlab, ylab, ... )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/ppc.mvgam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot mvgam posterior predictive checks for a specified series — ppc.mvgam","text":"object list object returned mvgam. See mvgam() ... par graphical parameters. newdata Optional dataframe list test data containing least 'series' 'time' forecast horizon, addition variables included linear predictor formula. included, observed values test data compared model's forecast distribution exploring biases model predictions. Note useful newdata also included fitting original model. data_test Deprecated. Still works place newdata users recommended use newdata instead seamless integration R workflows series integer specifying series set plotted type character specifying type posterior predictive check calculate plot. Valid options : 'rootogram', 'mean', 'hist', 'density', 'prop_zero', 'pit' 'cdf' n_bins integer specifying number bins use binning observed values plotting rootogram histogram. Default 50 bins rootogram, means >50 unique observed values, bins used prevent overplotting facilitate interpretation. Default histogram use number bins returned call hist base R legend_position location may also specified setting x single keyword list \"bottomright\", \"bottom\", \"bottomleft\", \"left\", \"topleft\", \"top\", \"topright\", \"right\" \"center\". places legend inside plot frame given location. alternatively, use \"none\" hide legend. xlab label x axis. ylab label y axis.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/ppc.mvgam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot mvgam posterior predictive checks for a specified series — ppc.mvgam","text":"base R graphics plot showing either posterior rootogram (type == 'rootogram'), predicted vs observed mean series (type == 'mean'), predicted vs observed proportion zeroes series (type == 'prop_zero'),predicted vs observed histogram series (type == 'hist'), kernel density empirical CDF estimates posterior predictions (type == 'density' type == 'cdf') Probability Integral Transform histogram (type == 'pit').","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/ppc.mvgam.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot mvgam posterior predictive checks for a specified series — ppc.mvgam","text":"Posterior predictions drawn fitted mvgam compared empirical distribution observed data specified series help evaluate model's ability generate unbiased predictions. plots apart 'rootogram', posterior predictions can also compared sample observations long observations included 'data_test' original model fit supplied . Rootograms currently plotted using 'hanging' style","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/predict.mvgam.html","id":null,"dir":"Reference","previous_headings":"","what":"Predict from the GAM component of an mvgam model — predict.mvgam","title":"Predict from the GAM component of an mvgam model — predict.mvgam","text":"Predict GAM component mvgam model","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/predict.mvgam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Predict from the GAM component of an mvgam model — predict.mvgam","text":"","code":"# S3 method for mvgam predict(object, newdata, data_test, type = \"link\", n_cores = 1, ...)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/predict.mvgam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Predict from the GAM component of an mvgam model — predict.mvgam","text":"object list object returned mvgam newdata Optional dataframe list test data containing variables included linear predictor formula. supplied, predictions generated original observations used model fit. data_test Deprecated. Still works place newdata users recommended use newdata instead seamless integration R workflows type value link (default) linear predictor calculated link scale. expected used, predictions reflect expectation response (mean) ignore uncertainty observation process. response used, predictions take uncertainty observation process account return predictions outcome scale n_cores integer specifying number cores generating predictions parallel ... Ignored","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/predict.mvgam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Predict from the GAM component of an mvgam model — predict.mvgam","text":"matrix dimension n_samples x new_obs, n_samples number posterior samples fitted object n_obs number test observations newdata","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/predict.mvgam.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Predict from the GAM component of an mvgam model — predict.mvgam","text":"Note types predictions, expected uncertainty process model accounted using draws trend SD parameters. trend_formula supplied model, predictions component also incorporated. trend predictions ignore autocorrelation coefficients GP length scale coefficients, ultimately assuming process stationary. method similar types posterior predictions returned brms models using autocorrelated error predictions newdata. function therefore suited posterior simulation GAM components mvgam model, forecasting functions plot_mvgam_fc forecast.mvgam better suited generate h-step ahead forecasts respect temporal dynamics estimated latent trends.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/print.mvgam.html","id":null,"dir":"Reference","previous_headings":"","what":"Summary for a fitted mvgam object — print.mvgam","title":"Summary for a fitted mvgam object — print.mvgam","text":"function takes fitted mvgam object prints quick summary","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/print.mvgam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Summary for a fitted mvgam object — print.mvgam","text":"","code":"# S3 method for mvgam print(x, ...)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/print.mvgam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Summary for a fitted mvgam object — print.mvgam","text":"x list object returned mvgam ... Ignored","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/print.mvgam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Summary for a fitted mvgam object — print.mvgam","text":"list printed -screen","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/print.mvgam.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Summary for a fitted mvgam object — print.mvgam","text":"brief summary model's call printed","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/print.mvgam.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Summary for a fitted mvgam object — print.mvgam","text":"Nicholas J Clark","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/score.mvgam_forecast.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute probabilistic forecast scores for mvgam objects — score.mvgam_forecast","title":"Compute probabilistic forecast scores for mvgam objects — score.mvgam_forecast","text":"Compute probabilistic forecast scores mvgam objects","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/score.mvgam_forecast.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute probabilistic forecast scores for mvgam objects — score.mvgam_forecast","text":"","code":"# S3 method for mvgam_forecast score(object, score = \"crps\", log = FALSE, weights, interval_width = 0.9, ...) score(object, ...)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/score.mvgam_forecast.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute probabilistic forecast scores for mvgam objects — score.mvgam_forecast","text":"object mvgam_forecast object. See forecast.mvgam(). score character specifying type ranked probability score use evaluation. Options : variogram, drps crps log logical. forecasts truths logged prior scoring? often appropriate comparing performance models series vary observation ranges weights optional vector weights (length(weights) == n_series) weighting pairwise correlations evaluating variogram score multivariate forecasts. Useful -weighting series larger magnitude observations less interest forecasting. Ignored score != 'variogram' interval_width proportional value [0.05,0.95] defining forecast interval calculating coverage ... Ignored","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/score.mvgam_forecast.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute probabilistic forecast scores for mvgam objects — score.mvgam_forecast","text":"list containing scores 90% interval coverages per forecast horizon. score %% c('drps', 'crps'), list also contain return sum series-level scores per horizon. score == 'variogram', series-level scores computed score returned series. scores, in_interval column series-level slot binary indicator whether true value within forecast's corresponding posterior empirical quantiles","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/score.mvgam_forecast.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compute probabilistic forecast scores for mvgam objects — score.mvgam_forecast","text":"","code":"if (FALSE) { #Simulate observations for three count-valued time series data <- sim_mvgam() #Fit a dynamic model using 'newdata' to automatically produce forecasts mod <- mvgam(y ~ 1, trend_model = 'RW', data = data$data_train, newdata = data$data_test) #Extract forecasts into a 'mvgam_forecast' object fc <- forecast(mod) #Score forecasts score(fc, score = 'drps') }"},{"path":"https://nicholasjclark.github.io/mvgam/reference/series_to_mvgam.html","id":null,"dir":"Reference","previous_headings":"","what":"This function converts univariate or multivariate time series (xts or ts objects)\r\nto the format necessary for mvgam — series_to_mvgam","title":"This function converts univariate or multivariate time series (xts or ts objects)\r\nto the format necessary for mvgam — series_to_mvgam","text":"function converts univariate multivariate time series (xts ts objects) format necessary mvgam","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/series_to_mvgam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"This function converts univariate or multivariate time series (xts or ts objects)\r\nto the format necessary for mvgam — series_to_mvgam","text":"","code":"series_to_mvgam(series, freq, train_prop = 0.85)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/series_to_mvgam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"This function converts univariate or multivariate time series (xts or ts objects)\r\nto the format necessary for mvgam — series_to_mvgam","text":"series xts ts object converted mvgam format freq integer. seasonal frequency series train_prop numeric stating proportion data use training. 0.25 0.95","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/series_to_mvgam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"This function converts univariate or multivariate time series (xts or ts objects)\r\nto the format necessary for mvgam — series_to_mvgam","text":"list object containing outputs needed mvgam, including 'data_train' 'data_test'","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/series_to_mvgam.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"This function converts univariate or multivariate time series (xts or ts objects)\r\nto the format necessary for mvgam — series_to_mvgam","text":"","code":"# A ts object example data(\"sunspots\") series <- cbind(sunspots, sunspots) colnames(series) <- c('blood', 'bone') head(series) #> blood bone #> [1,] 58.0 58.0 #> [2,] 62.6 62.6 #> [3,] 70.0 70.0 #> [4,] 55.7 55.7 #> [5,] 85.0 85.0 #> [6,] 83.5 83.5 series_to_mvgam(series, frequency(series), 0.85) #> $data_train #> y season year date series time #> 1 58.0 1 1749 1749-01-01 00:00:00 blood 1 #> 2 58.0 1 1749 1749-01-01 00:00:00 bone 1 #> 3 62.6 2 1749 1749-01-31 10:00:00 blood 2 #> 4 62.6 2 1749 1749-01-31 10:00:00 bone 2 #> 5 70.0 3 1749 1749-03-02 20:00:01 blood 3 #> 6 70.0 3 1749 1749-03-02 20:00:01 bone 3 #> 7 55.7 4 1749 1749-04-02 06:00:00 blood 4 #> 8 55.7 4 1749 1749-04-02 06:00:00 bone 4 #> 9 85.0 5 1749 1749-05-02 16:00:00 blood 5 #> 10 85.0 5 1749 1749-05-02 16:00:00 bone 5 #> 11 83.5 6 1749 1749-06-02 02:00:01 blood 6 #> 12 83.5 6 1749 1749-06-02 02:00:01 bone 6 #> 13 94.8 7 1749 1749-07-02 12:00:00 blood 7 #> 14 94.8 7 1749 1749-07-02 12:00:00 bone 7 #> 15 66.3 8 1749 1749-08-01 22:00:00 blood 8 #> 16 66.3 8 1749 1749-08-01 22:00:00 bone 8 #> 17 75.9 9 1749 1749-09-01 08:00:01 blood 9 #> 18 75.9 9 1749 1749-09-01 08:00:01 bone 9 #> 19 75.5 10 1749 1749-10-01 18:00:00 blood 10 #> 20 75.5 10 1749 1749-10-01 18:00:00 bone 10 #> 21 158.6 11 1749 1749-11-01 04:00:00 blood 11 #> 22 158.6 11 1749 1749-11-01 04:00:00 bone 11 #> 23 85.2 12 1749 1749-12-01 14:00:01 blood 12 #> 24 85.2 12 1749 1749-12-01 14:00:01 bone 12 #> 25 73.3 1 1750 1750-01-01 00:00:00 blood 13 #> 26 73.3 1 1750 1750-01-01 00:00:00 bone 13 #> 27 75.9 2 1750 1750-01-31 10:00:00 blood 14 #> 28 75.9 2 1750 1750-01-31 10:00:00 bone 14 #> 29 89.2 3 1750 1750-03-02 20:00:01 blood 15 #> 30 89.2 3 1750 1750-03-02 20:00:01 bone 15 #> 31 88.3 4 1750 1750-04-02 06:00:00 blood 16 #> 32 88.3 4 1750 1750-04-02 06:00:00 bone 16 #> 33 90.0 5 1750 1750-05-02 16:00:00 blood 17 #> 34 90.0 5 1750 1750-05-02 16:00:00 bone 17 #> 35 100.0 6 1750 1750-06-02 02:00:01 blood 18 #> 36 100.0 6 1750 1750-06-02 02:00:01 bone 18 #> 37 85.4 7 1750 1750-07-02 12:00:00 blood 19 #> 38 85.4 7 1750 1750-07-02 12:00:00 bone 19 #> 39 103.0 8 1750 1750-08-01 22:00:00 blood 20 #> 40 103.0 8 1750 1750-08-01 22:00:00 bone 20 #> 41 91.2 9 1750 1750-09-01 08:00:01 blood 21 #> 42 91.2 9 1750 1750-09-01 08:00:01 bone 21 #> 43 65.7 10 1750 1750-10-01 18:00:00 blood 22 #> 44 65.7 10 1750 1750-10-01 18:00:00 bone 22 #> 45 63.3 11 1750 1750-11-01 04:00:00 blood 23 #> 46 63.3 11 1750 1750-11-01 04:00:00 bone 23 #> 47 75.4 12 1750 1750-12-01 14:00:01 blood 24 #> 48 75.4 12 1750 1750-12-01 14:00:01 bone 24 #> 49 70.0 1 1751 1751-01-01 00:00:00 blood 25 #> 50 70.0 1 1751 1751-01-01 00:00:00 bone 25 #> 51 43.5 2 1751 1751-01-31 10:00:00 blood 26 #> 52 43.5 2 1751 1751-01-31 10:00:00 bone 26 #> 53 45.3 3 1751 1751-03-02 20:00:01 blood 27 #> 54 45.3 3 1751 1751-03-02 20:00:01 bone 27 #> 55 56.4 4 1751 1751-04-02 06:00:00 blood 28 #> 56 56.4 4 1751 1751-04-02 06:00:00 bone 28 #> 57 60.7 5 1751 1751-05-02 16:00:00 blood 29 #> 58 60.7 5 1751 1751-05-02 16:00:00 bone 29 #> 59 50.7 6 1751 1751-06-02 02:00:01 blood 30 #> 60 50.7 6 1751 1751-06-02 02:00:01 bone 30 #> 61 66.3 7 1751 1751-07-02 12:00:00 blood 31 #> 62 66.3 7 1751 1751-07-02 12:00:00 bone 31 #> 63 59.8 8 1751 1751-08-01 22:00:00 blood 32 #> 64 59.8 8 1751 1751-08-01 22:00:00 bone 32 #> 65 23.5 9 1751 1751-09-01 08:00:01 blood 33 #> 66 23.5 9 1751 1751-09-01 08:00:01 bone 33 #> 67 23.2 10 1751 1751-10-01 18:00:00 blood 34 #> 68 23.2 10 1751 1751-10-01 18:00:00 bone 34 #> 69 28.5 11 1751 1751-11-01 04:00:00 blood 35 #> 70 28.5 11 1751 1751-11-01 04:00:00 bone 35 #> 71 44.0 12 1751 1751-12-01 14:00:01 blood 36 #> 72 44.0 12 1751 1751-12-01 14:00:01 bone 36 #> 73 35.0 1 1752 1752-01-01 00:00:00 blood 37 #> 74 35.0 1 1752 1752-01-01 00:00:00 bone 37 #> 75 50.0 2 1752 1752-01-31 12:00:00 blood 38 #> 76 50.0 2 1752 1752-01-31 12:00:00 bone 38 #> 77 71.0 3 1752 1752-03-02 00:00:01 blood 39 #> 78 71.0 3 1752 1752-03-02 00:00:01 bone 39 #> 79 59.3 4 1752 1752-04-01 12:00:00 blood 40 #> 80 59.3 4 1752 1752-04-01 12:00:00 bone 40 #> 81 59.7 5 1752 1752-05-02 00:00:00 blood 41 #> 82 59.7 5 1752 1752-05-02 00:00:00 bone 41 #> 83 39.6 6 1752 1752-06-01 12:00:01 blood 42 #> 84 39.6 6 1752 1752-06-01 12:00:01 bone 42 #> 85 78.4 7 1752 1752-07-02 00:00:00 blood 43 #> 86 78.4 7 1752 1752-07-02 00:00:00 bone 43 #> 87 29.3 8 1752 1752-08-01 12:00:00 blood 44 #> 88 29.3 8 1752 1752-08-01 12:00:00 bone 44 #> 89 27.1 9 1752 1752-09-01 00:00:01 blood 45 #> 90 27.1 9 1752 1752-09-01 00:00:01 bone 45 #> 91 46.6 10 1752 1752-10-01 12:00:00 blood 46 #> 92 46.6 10 1752 1752-10-01 12:00:00 bone 46 #> 93 37.6 11 1752 1752-11-01 00:00:00 blood 47 #> 94 37.6 11 1752 1752-11-01 00:00:00 bone 47 #> 95 40.0 12 1752 1752-12-01 12:00:01 blood 48 #> 96 40.0 12 1752 1752-12-01 12:00:01 bone 48 #> 97 44.0 1 1753 1753-01-01 00:00:00 blood 49 #> 98 44.0 1 1753 1753-01-01 00:00:00 bone 49 #> 99 32.0 2 1753 1753-01-31 10:00:00 blood 50 #> 100 32.0 2 1753 1753-01-31 10:00:00 bone 50 #> 101 45.7 3 1753 1753-03-02 20:00:01 blood 51 #> 102 45.7 3 1753 1753-03-02 20:00:01 bone 51 #> 103 38.0 4 1753 1753-04-02 06:00:00 blood 52 #> 104 38.0 4 1753 1753-04-02 06:00:00 bone 52 #> 105 36.0 5 1753 1753-05-02 16:00:00 blood 53 #> 106 36.0 5 1753 1753-05-02 16:00:00 bone 53 #> 107 31.7 6 1753 1753-06-02 02:00:01 blood 54 #> 108 31.7 6 1753 1753-06-02 02:00:01 bone 54 #> 109 22.2 7 1753 1753-07-02 12:00:00 blood 55 #> 110 22.2 7 1753 1753-07-02 12:00:00 bone 55 #> 111 39.0 8 1753 1753-08-01 22:00:00 blood 56 #> 112 39.0 8 1753 1753-08-01 22:00:00 bone 56 #> 113 28.0 9 1753 1753-09-01 08:00:01 blood 57 #> 114 28.0 9 1753 1753-09-01 08:00:01 bone 57 #> 115 25.0 10 1753 1753-10-01 18:00:00 blood 58 #> 116 25.0 10 1753 1753-10-01 18:00:00 bone 58 #> 117 20.0 11 1753 1753-11-01 04:00:00 blood 59 #> 118 20.0 11 1753 1753-11-01 04:00:00 bone 59 #> 119 6.7 12 1753 1753-12-01 14:00:01 blood 60 #> 120 6.7 12 1753 1753-12-01 14:00:01 bone 60 #> 121 0.0 1 1754 1754-01-01 00:00:00 blood 61 #> 122 0.0 1 1754 1754-01-01 00:00:00 bone 61 #> 123 3.0 2 1754 1754-01-31 10:00:00 blood 62 #> 124 3.0 2 1754 1754-01-31 10:00:00 bone 62 #> 125 1.7 3 1754 1754-03-02 20:00:01 blood 63 #> 126 1.7 3 1754 1754-03-02 20:00:01 bone 63 #> 127 13.7 4 1754 1754-04-02 06:00:00 blood 64 #> 128 13.7 4 1754 1754-04-02 06:00:00 bone 64 #> 129 20.7 5 1754 1754-05-02 16:00:00 blood 65 #> 130 20.7 5 1754 1754-05-02 16:00:00 bone 65 #> 131 26.7 6 1754 1754-06-02 02:00:01 blood 66 #> 132 26.7 6 1754 1754-06-02 02:00:01 bone 66 #> 133 18.8 7 1754 1754-07-02 12:00:00 blood 67 #> 134 18.8 7 1754 1754-07-02 12:00:00 bone 67 #> 135 12.3 8 1754 1754-08-01 22:00:00 blood 68 #> 136 12.3 8 1754 1754-08-01 22:00:00 bone 68 #> 137 8.2 9 1754 1754-09-01 08:00:01 blood 69 #> 138 8.2 9 1754 1754-09-01 08:00:01 bone 69 #> 139 24.1 10 1754 1754-10-01 18:00:00 blood 70 #> 140 24.1 10 1754 1754-10-01 18:00:00 bone 70 #> 141 13.2 11 1754 1754-11-01 04:00:00 blood 71 #> 142 13.2 11 1754 1754-11-01 04:00:00 bone 71 #> 143 4.2 12 1754 1754-12-01 14:00:01 blood 72 #> 144 4.2 12 1754 1754-12-01 14:00:01 bone 72 #> 145 10.2 1 1755 1755-01-01 00:00:00 blood 73 #> 146 10.2 1 1755 1755-01-01 00:00:00 bone 73 #> 147 11.2 2 1755 1755-01-31 10:00:00 blood 74 #> 148 11.2 2 1755 1755-01-31 10:00:00 bone 74 #> 149 6.8 3 1755 1755-03-02 20:00:01 blood 75 #> 150 6.8 3 1755 1755-03-02 20:00:01 bone 75 #> 151 6.5 4 1755 1755-04-02 06:00:00 blood 76 #> 152 6.5 4 1755 1755-04-02 06:00:00 bone 76 #> 153 0.0 5 1755 1755-05-02 16:00:00 blood 77 #> 154 0.0 5 1755 1755-05-02 16:00:00 bone 77 #> 155 0.0 6 1755 1755-06-02 02:00:01 blood 78 #> 156 0.0 6 1755 1755-06-02 02:00:01 bone 78 #> 157 8.6 7 1755 1755-07-02 12:00:00 blood 79 #> 158 8.6 7 1755 1755-07-02 12:00:00 bone 79 #> 159 3.2 8 1755 1755-08-01 22:00:00 blood 80 #> 160 3.2 8 1755 1755-08-01 22:00:00 bone 80 #> 161 17.8 9 1755 1755-09-01 08:00:01 blood 81 #> 162 17.8 9 1755 1755-09-01 08:00:01 bone 81 #> 163 23.7 10 1755 1755-10-01 18:00:00 blood 82 #> 164 23.7 10 1755 1755-10-01 18:00:00 bone 82 #> 165 6.8 11 1755 1755-11-01 04:00:00 blood 83 #> 166 6.8 11 1755 1755-11-01 04:00:00 bone 83 #> 167 20.0 12 1755 1755-12-01 14:00:01 blood 84 #> 168 20.0 12 1755 1755-12-01 14:00:01 bone 84 #> 169 12.5 1 1756 1756-01-01 00:00:00 blood 85 #> 170 12.5 1 1756 1756-01-01 00:00:00 bone 85 #> 171 7.1 2 1756 1756-01-31 12:00:00 blood 86 #> 172 7.1 2 1756 1756-01-31 12:00:00 bone 86 #> 173 5.4 3 1756 1756-03-02 00:00:01 blood 87 #> 174 5.4 3 1756 1756-03-02 00:00:01 bone 87 #> 175 9.4 4 1756 1756-04-01 12:00:00 blood 88 #> 176 9.4 4 1756 1756-04-01 12:00:00 bone 88 #> 177 12.5 5 1756 1756-05-02 00:00:00 blood 89 #> 178 12.5 5 1756 1756-05-02 00:00:00 bone 89 #> 179 12.9 6 1756 1756-06-01 12:00:01 blood 90 #> 180 12.9 6 1756 1756-06-01 12:00:01 bone 90 #> 181 3.6 7 1756 1756-07-02 00:00:00 blood 91 #> 182 3.6 7 1756 1756-07-02 00:00:00 bone 91 #> 183 6.4 8 1756 1756-08-01 12:00:00 blood 92 #> 184 6.4 8 1756 1756-08-01 12:00:00 bone 92 #> 185 11.8 9 1756 1756-09-01 00:00:01 blood 93 #> 186 11.8 9 1756 1756-09-01 00:00:01 bone 93 #> 187 14.3 10 1756 1756-10-01 12:00:00 blood 94 #> 188 14.3 10 1756 1756-10-01 12:00:00 bone 94 #> 189 17.0 11 1756 1756-11-01 00:00:00 blood 95 #> 190 17.0 11 1756 1756-11-01 00:00:00 bone 95 #> 191 9.4 12 1756 1756-12-01 12:00:01 blood 96 #> 192 9.4 12 1756 1756-12-01 12:00:01 bone 96 #> 193 14.1 1 1757 1757-01-01 00:00:00 blood 97 #> 194 14.1 1 1757 1757-01-01 00:00:00 bone 97 #> 195 21.2 2 1757 1757-01-31 10:00:00 blood 98 #> 196 21.2 2 1757 1757-01-31 10:00:00 bone 98 #> 197 26.2 3 1757 1757-03-02 20:00:01 blood 99 #> 198 26.2 3 1757 1757-03-02 20:00:01 bone 99 #> 199 30.0 4 1757 1757-04-02 06:00:00 blood 100 #> 200 30.0 4 1757 1757-04-02 06:00:00 bone 100 #> 201 38.1 5 1757 1757-05-02 16:00:00 blood 101 #> 202 38.1 5 1757 1757-05-02 16:00:00 bone 101 #> 203 12.8 6 1757 1757-06-02 02:00:01 blood 102 #> 204 12.8 6 1757 1757-06-02 02:00:01 bone 102 #> 205 25.0 7 1757 1757-07-02 12:00:00 blood 103 #> 206 25.0 7 1757 1757-07-02 12:00:00 bone 103 #> 207 51.3 8 1757 1757-08-01 22:00:00 blood 104 #> 208 51.3 8 1757 1757-08-01 22:00:00 bone 104 #> 209 39.7 9 1757 1757-09-01 08:00:01 blood 105 #> 210 39.7 9 1757 1757-09-01 08:00:01 bone 105 #> 211 32.5 10 1757 1757-10-01 18:00:00 blood 106 #> 212 32.5 10 1757 1757-10-01 18:00:00 bone 106 #> 213 64.7 11 1757 1757-11-01 04:00:00 blood 107 #> 214 64.7 11 1757 1757-11-01 04:00:00 bone 107 #> 215 33.5 12 1757 1757-12-01 14:00:01 blood 108 #> 216 33.5 12 1757 1757-12-01 14:00:01 bone 108 #> 217 37.6 1 1758 1758-01-01 00:00:00 blood 109 #> 218 37.6 1 1758 1758-01-01 00:00:00 bone 109 #> 219 52.0 2 1758 1758-01-31 10:00:00 blood 110 #> 220 52.0 2 1758 1758-01-31 10:00:00 bone 110 #> 221 49.0 3 1758 1758-03-02 20:00:01 blood 111 #> 222 49.0 3 1758 1758-03-02 20:00:01 bone 111 #> 223 72.3 4 1758 1758-04-02 06:00:00 blood 112 #> 224 72.3 4 1758 1758-04-02 06:00:00 bone 112 #> 225 46.4 5 1758 1758-05-02 16:00:00 blood 113 #> 226 46.4 5 1758 1758-05-02 16:00:00 bone 113 #> 227 45.0 6 1758 1758-06-02 02:00:01 blood 114 #> 228 45.0 6 1758 1758-06-02 02:00:01 bone 114 #> 229 44.0 7 1758 1758-07-02 12:00:00 blood 115 #> 230 44.0 7 1758 1758-07-02 12:00:00 bone 115 #> 231 38.7 8 1758 1758-08-01 22:00:00 blood 116 #> 232 38.7 8 1758 1758-08-01 22:00:00 bone 116 #> 233 62.5 9 1758 1758-09-01 08:00:01 blood 117 #> 234 62.5 9 1758 1758-09-01 08:00:01 bone 117 #> 235 37.7 10 1758 1758-10-01 18:00:00 blood 118 #> 236 37.7 10 1758 1758-10-01 18:00:00 bone 118 #> 237 43.0 11 1758 1758-11-01 04:00:00 blood 119 #> 238 43.0 11 1758 1758-11-01 04:00:00 bone 119 #> 239 43.0 12 1758 1758-12-01 14:00:01 blood 120 #> 240 43.0 12 1758 1758-12-01 14:00:01 bone 120 #> 241 48.3 1 1759 1759-01-01 00:00:00 blood 121 #> 242 48.3 1 1759 1759-01-01 00:00:00 bone 121 #> 243 44.0 2 1759 1759-01-31 10:00:00 blood 122 #> 244 44.0 2 1759 1759-01-31 10:00:00 bone 122 #> 245 46.8 3 1759 1759-03-02 20:00:01 blood 123 #> 246 46.8 3 1759 1759-03-02 20:00:01 bone 123 #> 247 47.0 4 1759 1759-04-02 06:00:00 blood 124 #> 248 47.0 4 1759 1759-04-02 06:00:00 bone 124 #> 249 49.0 5 1759 1759-05-02 16:00:00 blood 125 #> 250 49.0 5 1759 1759-05-02 16:00:00 bone 125 #> 251 50.0 6 1759 1759-06-02 02:00:01 blood 126 #> 252 50.0 6 1759 1759-06-02 02:00:01 bone 126 #> 253 51.0 7 1759 1759-07-02 12:00:00 blood 127 #> 254 51.0 7 1759 1759-07-02 12:00:00 bone 127 #> 255 71.3 8 1759 1759-08-01 22:00:00 blood 128 #> 256 71.3 8 1759 1759-08-01 22:00:00 bone 128 #> 257 77.2 9 1759 1759-09-01 08:00:01 blood 129 #> 258 77.2 9 1759 1759-09-01 08:00:01 bone 129 #> 259 59.7 10 1759 1759-10-01 18:00:00 blood 130 #> 260 59.7 10 1759 1759-10-01 18:00:00 bone 130 #> 261 46.3 11 1759 1759-11-01 04:00:00 blood 131 #> 262 46.3 11 1759 1759-11-01 04:00:00 bone 131 #> 263 57.0 12 1759 1759-12-01 14:00:01 blood 132 #> 264 57.0 12 1759 1759-12-01 14:00:01 bone 132 #> 265 67.3 1 1760 1760-01-01 00:00:00 blood 133 #> 266 67.3 1 1760 1760-01-01 00:00:00 bone 133 #> 267 59.5 2 1760 1760-01-31 12:00:00 blood 134 #> 268 59.5 2 1760 1760-01-31 12:00:00 bone 134 #> 269 74.7 3 1760 1760-03-02 00:00:01 blood 135 #> 270 74.7 3 1760 1760-03-02 00:00:01 bone 135 #> 271 58.3 4 1760 1760-04-01 12:00:00 blood 136 #> 272 58.3 4 1760 1760-04-01 12:00:00 bone 136 #> 273 72.0 5 1760 1760-05-02 00:00:00 blood 137 #> 274 72.0 5 1760 1760-05-02 00:00:00 bone 137 #> 275 48.3 6 1760 1760-06-01 12:00:01 blood 138 #> 276 48.3 6 1760 1760-06-01 12:00:01 bone 138 #> 277 66.0 7 1760 1760-07-02 00:00:00 blood 139 #> 278 66.0 7 1760 1760-07-02 00:00:00 bone 139 #> 279 75.6 8 1760 1760-08-01 12:00:00 blood 140 #> 280 75.6 8 1760 1760-08-01 12:00:00 bone 140 #> 281 61.3 9 1760 1760-09-01 00:00:01 blood 141 #> 282 61.3 9 1760 1760-09-01 00:00:01 bone 141 #> 283 50.6 10 1760 1760-10-01 12:00:00 blood 142 #> 284 50.6 10 1760 1760-10-01 12:00:00 bone 142 #> 285 59.7 11 1760 1760-11-01 00:00:00 blood 143 #> 286 59.7 11 1760 1760-11-01 00:00:00 bone 143 #> 287 61.0 12 1760 1760-12-01 12:00:01 blood 144 #> 288 61.0 12 1760 1760-12-01 12:00:01 bone 144 #> 289 70.0 1 1761 1761-01-01 00:00:00 blood 145 #> 290 70.0 1 1761 1761-01-01 00:00:00 bone 145 #> 291 91.0 2 1761 1761-01-31 10:00:00 blood 146 #> 292 91.0 2 1761 1761-01-31 10:00:00 bone 146 #> 293 80.7 3 1761 1761-03-02 20:00:01 blood 147 #> 294 80.7 3 1761 1761-03-02 20:00:01 bone 147 #> 295 71.7 4 1761 1761-04-02 06:00:00 blood 148 #> 296 71.7 4 1761 1761-04-02 06:00:00 bone 148 #> 297 107.2 5 1761 1761-05-02 16:00:00 blood 149 #> 298 107.2 5 1761 1761-05-02 16:00:00 bone 149 #> 299 99.3 6 1761 1761-06-02 02:00:01 blood 150 #> 300 99.3 6 1761 1761-06-02 02:00:01 bone 150 #> 301 94.1 7 1761 1761-07-02 12:00:00 blood 151 #> 302 94.1 7 1761 1761-07-02 12:00:00 bone 151 #> 303 91.1 8 1761 1761-08-01 22:00:00 blood 152 #> 304 91.1 8 1761 1761-08-01 22:00:00 bone 152 #> 305 100.7 9 1761 1761-09-01 08:00:01 blood 153 #> 306 100.7 9 1761 1761-09-01 08:00:01 bone 153 #> 307 88.7 10 1761 1761-10-01 18:00:00 blood 154 #> 308 88.7 10 1761 1761-10-01 18:00:00 bone 154 #> 309 89.7 11 1761 1761-11-01 04:00:00 blood 155 #> 310 89.7 11 1761 1761-11-01 04:00:00 bone 155 #> 311 46.0 12 1761 1761-12-01 14:00:01 blood 156 #> 312 46.0 12 1761 1761-12-01 14:00:01 bone 156 #> 313 43.8 1 1762 1762-01-01 00:00:00 blood 157 #> 314 43.8 1 1762 1762-01-01 00:00:00 bone 157 #> 315 72.8 2 1762 1762-01-31 10:00:00 blood 158 #> 316 72.8 2 1762 1762-01-31 10:00:00 bone 158 #> 317 45.7 3 1762 1762-03-02 20:00:01 blood 159 #> 318 45.7 3 1762 1762-03-02 20:00:01 bone 159 #> 319 60.2 4 1762 1762-04-02 06:00:00 blood 160 #> 320 60.2 4 1762 1762-04-02 06:00:00 bone 160 #> 321 39.9 5 1762 1762-05-02 16:00:00 blood 161 #> 322 39.9 5 1762 1762-05-02 16:00:00 bone 161 #> 323 77.1 6 1762 1762-06-02 02:00:01 blood 162 #> 324 77.1 6 1762 1762-06-02 02:00:01 bone 162 #> 325 33.8 7 1762 1762-07-02 12:00:00 blood 163 #> 326 33.8 7 1762 1762-07-02 12:00:00 bone 163 #> 327 67.7 8 1762 1762-08-01 22:00:00 blood 164 #> 328 67.7 8 1762 1762-08-01 22:00:00 bone 164 #> 329 68.5 9 1762 1762-09-01 08:00:01 blood 165 #> 330 68.5 9 1762 1762-09-01 08:00:01 bone 165 #> 331 69.3 10 1762 1762-10-01 18:00:00 blood 166 #> 332 69.3 10 1762 1762-10-01 18:00:00 bone 166 #> 333 77.8 11 1762 1762-11-01 04:00:00 blood 167 #> 334 77.8 11 1762 1762-11-01 04:00:00 bone 167 #> 335 77.2 12 1762 1762-12-01 14:00:01 blood 168 #> 336 77.2 12 1762 1762-12-01 14:00:01 bone 168 #> 337 56.5 1 1763 1763-01-01 00:00:00 blood 169 #> 338 56.5 1 1763 1763-01-01 00:00:00 bone 169 #> 339 31.9 2 1763 1763-01-31 10:00:00 blood 170 #> 340 31.9 2 1763 1763-01-31 10:00:00 bone 170 #> 341 34.2 3 1763 1763-03-02 20:00:01 blood 171 #> 342 34.2 3 1763 1763-03-02 20:00:01 bone 171 #> 343 32.9 4 1763 1763-04-02 06:00:00 blood 172 #> 344 32.9 4 1763 1763-04-02 06:00:00 bone 172 #> 345 32.7 5 1763 1763-05-02 16:00:00 blood 173 #> 346 32.7 5 1763 1763-05-02 16:00:00 bone 173 #> 347 35.8 6 1763 1763-06-02 02:00:01 blood 174 #> 348 35.8 6 1763 1763-06-02 02:00:01 bone 174 #> 349 54.2 7 1763 1763-07-02 12:00:00 blood 175 #> 350 54.2 7 1763 1763-07-02 12:00:00 bone 175 #> 351 26.5 8 1763 1763-08-01 22:00:00 blood 176 #> 352 26.5 8 1763 1763-08-01 22:00:00 bone 176 #> 353 68.1 9 1763 1763-09-01 08:00:01 blood 177 #> 354 68.1 9 1763 1763-09-01 08:00:01 bone 177 #> 355 46.3 10 1763 1763-10-01 18:00:00 blood 178 #> 356 46.3 10 1763 1763-10-01 18:00:00 bone 178 #> 357 60.9 11 1763 1763-11-01 04:00:00 blood 179 #> 358 60.9 11 1763 1763-11-01 04:00:00 bone 179 #> 359 61.4 12 1763 1763-12-01 14:00:01 blood 180 #> 360 61.4 12 1763 1763-12-01 14:00:01 bone 180 #> 361 59.7 1 1764 1764-01-01 00:00:00 blood 181 #> 362 59.7 1 1764 1764-01-01 00:00:00 bone 181 #> 363 59.7 2 1764 1764-01-31 12:00:00 blood 182 #> 364 59.7 2 1764 1764-01-31 12:00:00 bone 182 #> 365 40.2 3 1764 1764-03-02 00:00:01 blood 183 #> 366 40.2 3 1764 1764-03-02 00:00:01 bone 183 #> 367 34.4 4 1764 1764-04-01 12:00:00 blood 184 #> 368 34.4 4 1764 1764-04-01 12:00:00 bone 184 #> 369 44.3 5 1764 1764-05-02 00:00:00 blood 185 #> 370 44.3 5 1764 1764-05-02 00:00:00 bone 185 #> 371 30.0 6 1764 1764-06-01 12:00:01 blood 186 #> 372 30.0 6 1764 1764-06-01 12:00:01 bone 186 #> 373 30.0 7 1764 1764-07-02 00:00:00 blood 187 #> 374 30.0 7 1764 1764-07-02 00:00:00 bone 187 #> 375 30.0 8 1764 1764-08-01 12:00:00 blood 188 #> 376 30.0 8 1764 1764-08-01 12:00:00 bone 188 #> 377 28.2 9 1764 1764-09-01 00:00:01 blood 189 #> 378 28.2 9 1764 1764-09-01 00:00:01 bone 189 #> 379 28.0 10 1764 1764-10-01 12:00:00 blood 190 #> 380 28.0 10 1764 1764-10-01 12:00:00 bone 190 #> 381 26.0 11 1764 1764-11-01 00:00:00 blood 191 #> 382 26.0 11 1764 1764-11-01 00:00:00 bone 191 #> 383 25.7 12 1764 1764-12-01 12:00:01 blood 192 #> 384 25.7 12 1764 1764-12-01 12:00:01 bone 192 #> 385 24.0 1 1765 1765-01-01 00:00:00 blood 193 #> 386 24.0 1 1765 1765-01-01 00:00:00 bone 193 #> 387 26.0 2 1765 1765-01-31 10:00:00 blood 194 #> 388 26.0 2 1765 1765-01-31 10:00:00 bone 194 #> 389 25.0 3 1765 1765-03-02 20:00:01 blood 195 #> 390 25.0 3 1765 1765-03-02 20:00:01 bone 195 #> 391 22.0 4 1765 1765-04-02 06:00:00 blood 196 #> 392 22.0 4 1765 1765-04-02 06:00:00 bone 196 #> 393 20.2 5 1765 1765-05-02 16:00:00 blood 197 #> 394 20.2 5 1765 1765-05-02 16:00:00 bone 197 #> 395 20.0 6 1765 1765-06-02 02:00:01 blood 198 #> 396 20.0 6 1765 1765-06-02 02:00:01 bone 198 #> 397 27.0 7 1765 1765-07-02 12:00:00 blood 199 #> 398 27.0 7 1765 1765-07-02 12:00:00 bone 199 #> 399 29.7 8 1765 1765-08-01 22:00:00 blood 200 #> 400 29.7 8 1765 1765-08-01 22:00:00 bone 200 #> 401 16.0 9 1765 1765-09-01 08:00:01 blood 201 #> 402 16.0 9 1765 1765-09-01 08:00:01 bone 201 #> 403 14.0 10 1765 1765-10-01 18:00:00 blood 202 #> 404 14.0 10 1765 1765-10-01 18:00:00 bone 202 #> 405 14.0 11 1765 1765-11-01 04:00:00 blood 203 #> 406 14.0 11 1765 1765-11-01 04:00:00 bone 203 #> 407 13.0 12 1765 1765-12-01 14:00:01 blood 204 #> 408 13.0 12 1765 1765-12-01 14:00:01 bone 204 #> 409 12.0 1 1766 1766-01-01 00:00:00 blood 205 #> 410 12.0 1 1766 1766-01-01 00:00:00 bone 205 #> 411 11.0 2 1766 1766-01-31 10:00:00 blood 206 #> 412 11.0 2 1766 1766-01-31 10:00:00 bone 206 #> 413 36.6 3 1766 1766-03-02 20:00:01 blood 207 #> 414 36.6 3 1766 1766-03-02 20:00:01 bone 207 #> 415 6.0 4 1766 1766-04-02 06:00:00 blood 208 #> 416 6.0 4 1766 1766-04-02 06:00:00 bone 208 #> 417 26.8 5 1766 1766-05-02 16:00:00 blood 209 #> 418 26.8 5 1766 1766-05-02 16:00:00 bone 209 #> 419 3.0 6 1766 1766-06-02 02:00:01 blood 210 #> 420 3.0 6 1766 1766-06-02 02:00:01 bone 210 #> 421 3.3 7 1766 1766-07-02 12:00:00 blood 211 #> 422 3.3 7 1766 1766-07-02 12:00:00 bone 211 #> 423 4.0 8 1766 1766-08-01 22:00:00 blood 212 #> 424 4.0 8 1766 1766-08-01 22:00:00 bone 212 #> 425 4.3 9 1766 1766-09-01 08:00:01 blood 213 #> 426 4.3 9 1766 1766-09-01 08:00:01 bone 213 #> 427 5.0 10 1766 1766-10-01 18:00:00 blood 214 #> 428 5.0 10 1766 1766-10-01 18:00:00 bone 214 #> 429 5.7 11 1766 1766-11-01 04:00:00 blood 215 #> 430 5.7 11 1766 1766-11-01 04:00:00 bone 215 #> 431 19.2 12 1766 1766-12-01 14:00:01 blood 216 #> 432 19.2 12 1766 1766-12-01 14:00:01 bone 216 #> 433 27.4 1 1767 1767-01-01 00:00:00 blood 217 #> 434 27.4 1 1767 1767-01-01 00:00:00 bone 217 #> 435 30.0 2 1767 1767-01-31 10:00:00 blood 218 #> 436 30.0 2 1767 1767-01-31 10:00:00 bone 218 #> 437 43.0 3 1767 1767-03-02 20:00:01 blood 219 #> 438 43.0 3 1767 1767-03-02 20:00:01 bone 219 #> 439 32.9 4 1767 1767-04-02 06:00:00 blood 220 #> 440 32.9 4 1767 1767-04-02 06:00:00 bone 220 #> 441 29.8 5 1767 1767-05-02 16:00:00 blood 221 #> 442 29.8 5 1767 1767-05-02 16:00:00 bone 221 #> 443 33.3 6 1767 1767-06-02 02:00:01 blood 222 #> 444 33.3 6 1767 1767-06-02 02:00:01 bone 222 #> 445 21.9 7 1767 1767-07-02 12:00:00 blood 223 #> 446 21.9 7 1767 1767-07-02 12:00:00 bone 223 #> 447 40.8 8 1767 1767-08-01 22:00:00 blood 224 #> 448 40.8 8 1767 1767-08-01 22:00:00 bone 224 #> 449 42.7 9 1767 1767-09-01 08:00:01 blood 225 #> 450 42.7 9 1767 1767-09-01 08:00:01 bone 225 #> 451 44.1 10 1767 1767-10-01 18:00:00 blood 226 #> 452 44.1 10 1767 1767-10-01 18:00:00 bone 226 #> 453 54.7 11 1767 1767-11-01 04:00:00 blood 227 #> 454 54.7 11 1767 1767-11-01 04:00:00 bone 227 #> 455 53.3 12 1767 1767-12-01 14:00:01 blood 228 #> 456 53.3 12 1767 1767-12-01 14:00:01 bone 228 #> 457 53.5 1 1768 1768-01-01 00:00:00 blood 229 #> 458 53.5 1 1768 1768-01-01 00:00:00 bone 229 #> 459 66.1 2 1768 1768-01-31 12:00:00 blood 230 #> 460 66.1 2 1768 1768-01-31 12:00:00 bone 230 #> 461 46.3 3 1768 1768-03-02 00:00:01 blood 231 #> 462 46.3 3 1768 1768-03-02 00:00:01 bone 231 #> 463 42.7 4 1768 1768-04-01 12:00:00 blood 232 #> 464 42.7 4 1768 1768-04-01 12:00:00 bone 232 #> 465 77.7 5 1768 1768-05-02 00:00:00 blood 233 #> 466 77.7 5 1768 1768-05-02 00:00:00 bone 233 #> 467 77.4 6 1768 1768-06-01 12:00:01 blood 234 #> 468 77.4 6 1768 1768-06-01 12:00:01 bone 234 #> 469 52.6 7 1768 1768-07-02 00:00:00 blood 235 #> 470 52.6 7 1768 1768-07-02 00:00:00 bone 235 #> 471 66.8 8 1768 1768-08-01 12:00:00 blood 236 #> 472 66.8 8 1768 1768-08-01 12:00:00 bone 236 #> 473 74.8 9 1768 1768-09-01 00:00:01 blood 237 #> 474 74.8 9 1768 1768-09-01 00:00:01 bone 237 #> 475 77.8 10 1768 1768-10-01 12:00:00 blood 238 #> 476 77.8 10 1768 1768-10-01 12:00:00 bone 238 #> 477 90.6 11 1768 1768-11-01 00:00:00 blood 239 #> 478 90.6 11 1768 1768-11-01 00:00:00 bone 239 #> 479 111.8 12 1768 1768-12-01 12:00:01 blood 240 #> 480 111.8 12 1768 1768-12-01 12:00:01 bone 240 #> 481 73.9 1 1769 1769-01-01 00:00:00 blood 241 #> 482 73.9 1 1769 1769-01-01 00:00:00 bone 241 #> 483 64.2 2 1769 1769-01-31 10:00:00 blood 242 #> 484 64.2 2 1769 1769-01-31 10:00:00 bone 242 #> 485 64.3 3 1769 1769-03-02 20:00:01 blood 243 #> 486 64.3 3 1769 1769-03-02 20:00:01 bone 243 #> 487 96.7 4 1769 1769-04-02 06:00:00 blood 244 #> 488 96.7 4 1769 1769-04-02 06:00:00 bone 244 #> 489 73.6 5 1769 1769-05-02 16:00:00 blood 245 #> 490 73.6 5 1769 1769-05-02 16:00:00 bone 245 #> 491 94.4 6 1769 1769-06-02 02:00:01 blood 246 #> 492 94.4 6 1769 1769-06-02 02:00:01 bone 246 #> 493 118.6 7 1769 1769-07-02 12:00:00 blood 247 #> 494 118.6 7 1769 1769-07-02 12:00:00 bone 247 #> 495 120.3 8 1769 1769-08-01 22:00:00 blood 248 #> 496 120.3 8 1769 1769-08-01 22:00:00 bone 248 #> 497 148.8 9 1769 1769-09-01 08:00:01 blood 249 #> 498 148.8 9 1769 1769-09-01 08:00:01 bone 249 #> 499 158.2 10 1769 1769-10-01 18:00:00 blood 250 #> 500 158.2 10 1769 1769-10-01 18:00:00 bone 250 #> 501 148.1 11 1769 1769-11-01 04:00:00 blood 251 #> 502 148.1 11 1769 1769-11-01 04:00:00 bone 251 #> 503 112.0 12 1769 1769-12-01 14:00:01 blood 252 #> 504 112.0 12 1769 1769-12-01 14:00:01 bone 252 #> 505 104.0 1 1770 1770-01-01 00:00:00 blood 253 #> 506 104.0 1 1770 1770-01-01 00:00:00 bone 253 #> 507 142.5 2 1770 1770-01-31 10:00:00 blood 254 #> 508 142.5 2 1770 1770-01-31 10:00:00 bone 254 #> 509 80.1 3 1770 1770-03-02 20:00:01 blood 255 #> 510 80.1 3 1770 1770-03-02 20:00:01 bone 255 #> 511 51.0 4 1770 1770-04-02 06:00:00 blood 256 #> 512 51.0 4 1770 1770-04-02 06:00:00 bone 256 #> 513 70.1 5 1770 1770-05-02 16:00:00 blood 257 #> 514 70.1 5 1770 1770-05-02 16:00:00 bone 257 #> 515 83.3 6 1770 1770-06-02 02:00:01 blood 258 #> 516 83.3 6 1770 1770-06-02 02:00:01 bone 258 #> 517 109.8 7 1770 1770-07-02 12:00:00 blood 259 #> 518 109.8 7 1770 1770-07-02 12:00:00 bone 259 #> 519 126.3 8 1770 1770-08-01 22:00:00 blood 260 #> 520 126.3 8 1770 1770-08-01 22:00:00 bone 260 #> 521 104.4 9 1770 1770-09-01 08:00:01 blood 261 #> 522 104.4 9 1770 1770-09-01 08:00:01 bone 261 #> 523 103.6 10 1770 1770-10-01 18:00:00 blood 262 #> 524 103.6 10 1770 1770-10-01 18:00:00 bone 262 #> 525 132.2 11 1770 1770-11-01 04:00:00 blood 263 #> 526 132.2 11 1770 1770-11-01 04:00:00 bone 263 #> 527 102.3 12 1770 1770-12-01 14:00:01 blood 264 #> 528 102.3 12 1770 1770-12-01 14:00:01 bone 264 #> 529 36.0 1 1771 1771-01-01 00:00:00 blood 265 #> 530 36.0 1 1771 1771-01-01 00:00:00 bone 265 #> 531 46.2 2 1771 1771-01-31 10:00:00 blood 266 #> 532 46.2 2 1771 1771-01-31 10:00:00 bone 266 #> 533 46.7 3 1771 1771-03-02 20:00:01 blood 267 #> 534 46.7 3 1771 1771-03-02 20:00:01 bone 267 #> 535 64.9 4 1771 1771-04-02 06:00:00 blood 268 #> 536 64.9 4 1771 1771-04-02 06:00:00 bone 268 #> 537 152.7 5 1771 1771-05-02 16:00:00 blood 269 #> 538 152.7 5 1771 1771-05-02 16:00:00 bone 269 #> 539 119.5 6 1771 1771-06-02 02:00:01 blood 270 #> 540 119.5 6 1771 1771-06-02 02:00:01 bone 270 #> 541 67.7 7 1771 1771-07-02 12:00:00 blood 271 #> 542 67.7 7 1771 1771-07-02 12:00:00 bone 271 #> 543 58.5 8 1771 1771-08-01 22:00:00 blood 272 #> 544 58.5 8 1771 1771-08-01 22:00:00 bone 272 #> 545 101.4 9 1771 1771-09-01 08:00:01 blood 273 #> 546 101.4 9 1771 1771-09-01 08:00:01 bone 273 #> 547 90.0 10 1771 1771-10-01 18:00:00 blood 274 #> 548 90.0 10 1771 1771-10-01 18:00:00 bone 274 #> 549 99.7 11 1771 1771-11-01 04:00:00 blood 275 #> 550 99.7 11 1771 1771-11-01 04:00:00 bone 275 #> 551 95.7 12 1771 1771-12-01 14:00:01 blood 276 #> 552 95.7 12 1771 1771-12-01 14:00:01 bone 276 #> 553 100.9 1 1772 1772-01-01 00:00:00 blood 277 #> 554 100.9 1 1772 1772-01-01 00:00:00 bone 277 #> 555 90.8 2 1772 1772-01-31 12:00:00 blood 278 #> 556 90.8 2 1772 1772-01-31 12:00:00 bone 278 #> 557 31.1 3 1772 1772-03-02 00:00:01 blood 279 #> 558 31.1 3 1772 1772-03-02 00:00:01 bone 279 #> 559 92.2 4 1772 1772-04-01 12:00:00 blood 280 #> 560 92.2 4 1772 1772-04-01 12:00:00 bone 280 #> 561 38.0 5 1772 1772-05-02 00:00:00 blood 281 #> 562 38.0 5 1772 1772-05-02 00:00:00 bone 281 #> 563 57.0 6 1772 1772-06-01 12:00:01 blood 282 #> 564 57.0 6 1772 1772-06-01 12:00:01 bone 282 #> 565 77.3 7 1772 1772-07-02 00:00:00 blood 283 #> 566 77.3 7 1772 1772-07-02 00:00:00 bone 283 #> 567 56.2 8 1772 1772-08-01 12:00:00 blood 284 #> 568 56.2 8 1772 1772-08-01 12:00:00 bone 284 #> 569 50.5 9 1772 1772-09-01 00:00:01 blood 285 #> 570 50.5 9 1772 1772-09-01 00:00:01 bone 285 #> 571 78.6 10 1772 1772-10-01 12:00:00 blood 286 #> 572 78.6 10 1772 1772-10-01 12:00:00 bone 286 #> 573 61.3 11 1772 1772-11-01 00:00:00 blood 287 #> 574 61.3 11 1772 1772-11-01 00:00:00 bone 287 #> 575 64.0 12 1772 1772-12-01 12:00:01 blood 288 #> 576 64.0 12 1772 1772-12-01 12:00:01 bone 288 #> 577 54.6 1 1773 1773-01-01 00:00:00 blood 289 #> 578 54.6 1 1773 1773-01-01 00:00:00 bone 289 #> 579 29.0 2 1773 1773-01-31 10:00:00 blood 290 #> 580 29.0 2 1773 1773-01-31 10:00:00 bone 290 #> 581 51.2 3 1773 1773-03-02 20:00:01 blood 291 #> 582 51.2 3 1773 1773-03-02 20:00:01 bone 291 #> 583 32.9 4 1773 1773-04-02 06:00:00 blood 292 #> 584 32.9 4 1773 1773-04-02 06:00:00 bone 292 #> 585 41.1 5 1773 1773-05-02 16:00:00 blood 293 #> 586 41.1 5 1773 1773-05-02 16:00:00 bone 293 #> 587 28.4 6 1773 1773-06-02 02:00:01 blood 294 #> 588 28.4 6 1773 1773-06-02 02:00:01 bone 294 #> 589 27.7 7 1773 1773-07-02 12:00:00 blood 295 #> 590 27.7 7 1773 1773-07-02 12:00:00 bone 295 #> 591 12.7 8 1773 1773-08-01 22:00:00 blood 296 #> 592 12.7 8 1773 1773-08-01 22:00:00 bone 296 #> 593 29.3 9 1773 1773-09-01 08:00:01 blood 297 #> 594 29.3 9 1773 1773-09-01 08:00:01 bone 297 #> 595 26.3 10 1773 1773-10-01 18:00:00 blood 298 #> 596 26.3 10 1773 1773-10-01 18:00:00 bone 298 #> 597 40.9 11 1773 1773-11-01 04:00:00 blood 299 #> 598 40.9 11 1773 1773-11-01 04:00:00 bone 299 #> 599 43.2 12 1773 1773-12-01 14:00:01 blood 300 #> 600 43.2 12 1773 1773-12-01 14:00:01 bone 300 #> 601 46.8 1 1774 1774-01-01 00:00:00 blood 301 #> 602 46.8 1 1774 1774-01-01 00:00:00 bone 301 #> 603 65.4 2 1774 1774-01-31 10:00:00 blood 302 #> 604 65.4 2 1774 1774-01-31 10:00:00 bone 302 #> 605 55.7 3 1774 1774-03-02 20:00:01 blood 303 #> 606 55.7 3 1774 1774-03-02 20:00:01 bone 303 #> 607 43.8 4 1774 1774-04-02 06:00:00 blood 304 #> 608 43.8 4 1774 1774-04-02 06:00:00 bone 304 #> 609 51.3 5 1774 1774-05-02 16:00:00 blood 305 #> 610 51.3 5 1774 1774-05-02 16:00:00 bone 305 #> 611 28.5 6 1774 1774-06-02 02:00:01 blood 306 #> 612 28.5 6 1774 1774-06-02 02:00:01 bone 306 #> 613 17.5 7 1774 1774-07-02 12:00:00 blood 307 #> 614 17.5 7 1774 1774-07-02 12:00:00 bone 307 #> 615 6.6 8 1774 1774-08-01 22:00:00 blood 308 #> 616 6.6 8 1774 1774-08-01 22:00:00 bone 308 #> 617 7.9 9 1774 1774-09-01 08:00:01 blood 309 #> 618 7.9 9 1774 1774-09-01 08:00:01 bone 309 #> 619 14.0 10 1774 1774-10-01 18:00:00 blood 310 #> 620 14.0 10 1774 1774-10-01 18:00:00 bone 310 #> 621 17.7 11 1774 1774-11-01 04:00:00 blood 311 #> 622 17.7 11 1774 1774-11-01 04:00:00 bone 311 #> 623 12.2 12 1774 1774-12-01 14:00:01 blood 312 #> 624 12.2 12 1774 1774-12-01 14:00:01 bone 312 #> 625 4.4 1 1775 1775-01-01 00:00:00 blood 313 #> 626 4.4 1 1775 1775-01-01 00:00:00 bone 313 #> 627 0.0 2 1775 1775-01-31 10:00:00 blood 314 #> 628 0.0 2 1775 1775-01-31 10:00:00 bone 314 #> 629 11.6 3 1775 1775-03-02 20:00:01 blood 315 #> 630 11.6 3 1775 1775-03-02 20:00:01 bone 315 #> 631 11.2 4 1775 1775-04-02 06:00:00 blood 316 #> 632 11.2 4 1775 1775-04-02 06:00:00 bone 316 #> 633 3.9 5 1775 1775-05-02 16:00:00 blood 317 #> 634 3.9 5 1775 1775-05-02 16:00:00 bone 317 #> 635 12.3 6 1775 1775-06-02 02:00:01 blood 318 #> 636 12.3 6 1775 1775-06-02 02:00:01 bone 318 #> 637 1.0 7 1775 1775-07-02 12:00:00 blood 319 #> 638 1.0 7 1775 1775-07-02 12:00:00 bone 319 #> 639 7.9 8 1775 1775-08-01 22:00:00 blood 320 #> 640 7.9 8 1775 1775-08-01 22:00:00 bone 320 #> 641 3.2 9 1775 1775-09-01 08:00:01 blood 321 #> 642 3.2 9 1775 1775-09-01 08:00:01 bone 321 #> 643 5.6 10 1775 1775-10-01 18:00:00 blood 322 #> 644 5.6 10 1775 1775-10-01 18:00:00 bone 322 #> 645 15.1 11 1775 1775-11-01 04:00:00 blood 323 #> 646 15.1 11 1775 1775-11-01 04:00:00 bone 323 #> 647 7.9 12 1775 1775-12-01 14:00:01 blood 324 #> 648 7.9 12 1775 1775-12-01 14:00:01 bone 324 #> 649 21.7 1 1776 1776-01-01 00:00:00 blood 325 #> 650 21.7 1 1776 1776-01-01 00:00:00 bone 325 #> 651 11.6 2 1776 1776-01-31 12:00:00 blood 326 #> 652 11.6 2 1776 1776-01-31 12:00:00 bone 326 #> 653 6.3 3 1776 1776-03-02 00:00:01 blood 327 #> 654 6.3 3 1776 1776-03-02 00:00:01 bone 327 #> 655 21.8 4 1776 1776-04-01 12:00:00 blood 328 #> 656 21.8 4 1776 1776-04-01 12:00:00 bone 328 #> 657 11.2 5 1776 1776-05-02 00:00:00 blood 329 #> 658 11.2 5 1776 1776-05-02 00:00:00 bone 329 #> 659 19.0 6 1776 1776-06-01 12:00:01 blood 330 #> 660 19.0 6 1776 1776-06-01 12:00:01 bone 330 #> 661 1.0 7 1776 1776-07-02 00:00:00 blood 331 #> 662 1.0 7 1776 1776-07-02 00:00:00 bone 331 #> 663 24.2 8 1776 1776-08-01 12:00:00 blood 332 #> 664 24.2 8 1776 1776-08-01 12:00:00 bone 332 #> 665 16.0 9 1776 1776-09-01 00:00:01 blood 333 #> 666 16.0 9 1776 1776-09-01 00:00:01 bone 333 #> 667 30.0 10 1776 1776-10-01 12:00:00 blood 334 #> 668 30.0 10 1776 1776-10-01 12:00:00 bone 334 #> 669 35.0 11 1776 1776-11-01 00:00:00 blood 335 #> 670 35.0 11 1776 1776-11-01 00:00:00 bone 335 #> 671 40.0 12 1776 1776-12-01 12:00:01 blood 336 #> 672 40.0 12 1776 1776-12-01 12:00:01 bone 336 #> 673 45.0 1 1777 1777-01-01 00:00:00 blood 337 #> 674 45.0 1 1777 1777-01-01 00:00:00 bone 337 #> 675 36.5 2 1777 1777-01-31 10:00:00 blood 338 #> 676 36.5 2 1777 1777-01-31 10:00:00 bone 338 #> 677 39.0 3 1777 1777-03-02 20:00:01 blood 339 #> 678 39.0 3 1777 1777-03-02 20:00:01 bone 339 #> 679 95.5 4 1777 1777-04-02 06:00:00 blood 340 #> 680 95.5 4 1777 1777-04-02 06:00:00 bone 340 #> 681 80.3 5 1777 1777-05-02 16:00:00 blood 341 #> 682 80.3 5 1777 1777-05-02 16:00:00 bone 341 #> 683 80.7 6 1777 1777-06-02 02:00:01 blood 342 #> 684 80.7 6 1777 1777-06-02 02:00:01 bone 342 #> 685 95.0 7 1777 1777-07-02 12:00:00 blood 343 #> 686 95.0 7 1777 1777-07-02 12:00:00 bone 343 #> 687 112.0 8 1777 1777-08-01 22:00:00 blood 344 #> 688 112.0 8 1777 1777-08-01 22:00:00 bone 344 #> 689 116.2 9 1777 1777-09-01 08:00:01 blood 345 #> 690 116.2 9 1777 1777-09-01 08:00:01 bone 345 #> 691 106.5 10 1777 1777-10-01 18:00:00 blood 346 #> 692 106.5 10 1777 1777-10-01 18:00:00 bone 346 #> 693 146.0 11 1777 1777-11-01 04:00:00 blood 347 #> 694 146.0 11 1777 1777-11-01 04:00:00 bone 347 #> 695 157.3 12 1777 1777-12-01 14:00:01 blood 348 #> 696 157.3 12 1777 1777-12-01 14:00:01 bone 348 #> 697 177.3 1 1778 1778-01-01 00:00:00 blood 349 #> 698 177.3 1 1778 1778-01-01 00:00:00 bone 349 #> 699 109.3 2 1778 1778-01-31 10:00:00 blood 350 #> 700 109.3 2 1778 1778-01-31 10:00:00 bone 350 #> 701 134.0 3 1778 1778-03-02 20:00:01 blood 351 #> 702 134.0 3 1778 1778-03-02 20:00:01 bone 351 #> 703 145.0 4 1778 1778-04-02 06:00:00 blood 352 #> 704 145.0 4 1778 1778-04-02 06:00:00 bone 352 #> 705 238.9 5 1778 1778-05-02 16:00:00 blood 353 #> 706 238.9 5 1778 1778-05-02 16:00:00 bone 353 #> 707 171.6 6 1778 1778-06-02 02:00:01 blood 354 #> 708 171.6 6 1778 1778-06-02 02:00:01 bone 354 #> 709 153.0 7 1778 1778-07-02 12:00:00 blood 355 #> 710 153.0 7 1778 1778-07-02 12:00:00 bone 355 #> 711 140.0 8 1778 1778-08-01 22:00:00 blood 356 #> 712 140.0 8 1778 1778-08-01 22:00:00 bone 356 #> 713 171.7 9 1778 1778-09-01 08:00:01 blood 357 #> 714 171.7 9 1778 1778-09-01 08:00:01 bone 357 #> 715 156.3 10 1778 1778-10-01 18:00:00 blood 358 #> 716 156.3 10 1778 1778-10-01 18:00:00 bone 358 #> 717 150.3 11 1778 1778-11-01 04:00:00 blood 359 #> 718 150.3 11 1778 1778-11-01 04:00:00 bone 359 #> 719 105.0 12 1778 1778-12-01 14:00:01 blood 360 #> 720 105.0 12 1778 1778-12-01 14:00:01 bone 360 #> 721 114.7 1 1779 1779-01-01 00:00:00 blood 361 #> 722 114.7 1 1779 1779-01-01 00:00:00 bone 361 #> 723 165.7 2 1779 1779-01-31 10:00:00 blood 362 #> 724 165.7 2 1779 1779-01-31 10:00:00 bone 362 #> 725 118.0 3 1779 1779-03-02 20:00:01 blood 363 #> 726 118.0 3 1779 1779-03-02 20:00:01 bone 363 #> 727 145.0 4 1779 1779-04-02 06:00:00 blood 364 #> 728 145.0 4 1779 1779-04-02 06:00:00 bone 364 #> 729 140.0 5 1779 1779-05-02 16:00:00 blood 365 #> 730 140.0 5 1779 1779-05-02 16:00:00 bone 365 #> 731 113.7 6 1779 1779-06-02 02:00:01 blood 366 #> 732 113.7 6 1779 1779-06-02 02:00:01 bone 366 #> 733 143.0 7 1779 1779-07-02 12:00:00 blood 367 #> 734 143.0 7 1779 1779-07-02 12:00:00 bone 367 #> 735 112.0 8 1779 1779-08-01 22:00:00 blood 368 #> 736 112.0 8 1779 1779-08-01 22:00:00 bone 368 #> 737 111.0 9 1779 1779-09-01 08:00:01 blood 369 #> 738 111.0 9 1779 1779-09-01 08:00:01 bone 369 #> 739 124.0 10 1779 1779-10-01 18:00:00 blood 370 #> 740 124.0 10 1779 1779-10-01 18:00:00 bone 370 #> 741 114.0 11 1779 1779-11-01 04:00:00 blood 371 #> 742 114.0 11 1779 1779-11-01 04:00:00 bone 371 #> 743 110.0 12 1779 1779-12-01 14:00:01 blood 372 #> 744 110.0 12 1779 1779-12-01 14:00:01 bone 372 #> 745 70.0 1 1780 1780-01-01 00:00:00 blood 373 #> 746 70.0 1 1780 1780-01-01 00:00:00 bone 373 #> 747 98.0 2 1780 1780-01-31 12:00:00 blood 374 #> 748 98.0 2 1780 1780-01-31 12:00:00 bone 374 #> 749 98.0 3 1780 1780-03-02 00:00:01 blood 375 #> 750 98.0 3 1780 1780-03-02 00:00:01 bone 375 #> 751 95.0 4 1780 1780-04-01 12:00:00 blood 376 #> 752 95.0 4 1780 1780-04-01 12:00:00 bone 376 #> 753 107.2 5 1780 1780-05-02 00:00:00 blood 377 #> 754 107.2 5 1780 1780-05-02 00:00:00 bone 377 #> 755 88.0 6 1780 1780-06-01 12:00:01 blood 378 #> 756 88.0 6 1780 1780-06-01 12:00:01 bone 378 #> 757 86.0 7 1780 1780-07-02 00:00:00 blood 379 #> 758 86.0 7 1780 1780-07-02 00:00:00 bone 379 #> 759 86.0 8 1780 1780-08-01 12:00:00 blood 380 #> 760 86.0 8 1780 1780-08-01 12:00:00 bone 380 #> 761 93.7 9 1780 1780-09-01 00:00:01 blood 381 #> 762 93.7 9 1780 1780-09-01 00:00:01 bone 381 #> 763 77.0 10 1780 1780-10-01 12:00:00 blood 382 #> 764 77.0 10 1780 1780-10-01 12:00:00 bone 382 #> 765 60.0 11 1780 1780-11-01 00:00:00 blood 383 #> 766 60.0 11 1780 1780-11-01 00:00:00 bone 383 #> 767 58.7 12 1780 1780-12-01 12:00:01 blood 384 #> 768 58.7 12 1780 1780-12-01 12:00:01 bone 384 #> 769 98.7 1 1781 1781-01-01 00:00:00 blood 385 #> 770 98.7 1 1781 1781-01-01 00:00:00 bone 385 #> 771 74.7 2 1781 1781-01-31 10:00:00 blood 386 #> 772 74.7 2 1781 1781-01-31 10:00:00 bone 386 #> 773 53.0 3 1781 1781-03-02 20:00:01 blood 387 #> 774 53.0 3 1781 1781-03-02 20:00:01 bone 387 #> 775 68.3 4 1781 1781-04-02 06:00:00 blood 388 #> 776 68.3 4 1781 1781-04-02 06:00:00 bone 388 #> 777 104.7 5 1781 1781-05-02 16:00:00 blood 389 #> 778 104.7 5 1781 1781-05-02 16:00:00 bone 389 #> 779 97.7 6 1781 1781-06-02 02:00:01 blood 390 #> 780 97.7 6 1781 1781-06-02 02:00:01 bone 390 #> 781 73.5 7 1781 1781-07-02 12:00:00 blood 391 #> 782 73.5 7 1781 1781-07-02 12:00:00 bone 391 #> 783 66.0 8 1781 1781-08-01 22:00:00 blood 392 #> 784 66.0 8 1781 1781-08-01 22:00:00 bone 392 #> 785 51.0 9 1781 1781-09-01 08:00:01 blood 393 #> 786 51.0 9 1781 1781-09-01 08:00:01 bone 393 #> 787 27.3 10 1781 1781-10-01 18:00:00 blood 394 #> 788 27.3 10 1781 1781-10-01 18:00:00 bone 394 #> 789 67.0 11 1781 1781-11-01 04:00:00 blood 395 #> 790 67.0 11 1781 1781-11-01 04:00:00 bone 395 #> 791 35.2 12 1781 1781-12-01 14:00:01 blood 396 #> 792 35.2 12 1781 1781-12-01 14:00:01 bone 396 #> 793 54.0 1 1782 1782-01-01 00:00:00 blood 397 #> 794 54.0 1 1782 1782-01-01 00:00:00 bone 397 #> 795 37.5 2 1782 1782-01-31 10:00:00 blood 398 #> 796 37.5 2 1782 1782-01-31 10:00:00 bone 398 #> 797 37.0 3 1782 1782-03-02 20:00:01 blood 399 #> 798 37.0 3 1782 1782-03-02 20:00:01 bone 399 #> 799 41.0 4 1782 1782-04-02 06:00:00 blood 400 #> 800 41.0 4 1782 1782-04-02 06:00:00 bone 400 #> 801 54.3 5 1782 1782-05-02 16:00:00 blood 401 #> 802 54.3 5 1782 1782-05-02 16:00:00 bone 401 #> 803 38.0 6 1782 1782-06-02 02:00:01 blood 402 #> 804 38.0 6 1782 1782-06-02 02:00:01 bone 402 #> 805 37.0 7 1782 1782-07-02 12:00:00 blood 403 #> 806 37.0 7 1782 1782-07-02 12:00:00 bone 403 #> 807 44.0 8 1782 1782-08-01 22:00:00 blood 404 #> 808 44.0 8 1782 1782-08-01 22:00:00 bone 404 #> 809 34.0 9 1782 1782-09-01 08:00:01 blood 405 #> 810 34.0 9 1782 1782-09-01 08:00:01 bone 405 #> 811 23.2 10 1782 1782-10-01 18:00:00 blood 406 #> 812 23.2 10 1782 1782-10-01 18:00:00 bone 406 #> 813 31.5 11 1782 1782-11-01 04:00:00 blood 407 #> 814 31.5 11 1782 1782-11-01 04:00:00 bone 407 #> 815 30.0 12 1782 1782-12-01 14:00:01 blood 408 #> 816 30.0 12 1782 1782-12-01 14:00:01 bone 408 #> 817 28.0 1 1783 1783-01-01 00:00:00 blood 409 #> 818 28.0 1 1783 1783-01-01 00:00:00 bone 409 #> 819 38.7 2 1783 1783-01-31 10:00:00 blood 410 #> 820 38.7 2 1783 1783-01-31 10:00:00 bone 410 #> 821 26.7 3 1783 1783-03-02 20:00:01 blood 411 #> 822 26.7 3 1783 1783-03-02 20:00:01 bone 411 #> 823 28.3 4 1783 1783-04-02 06:00:00 blood 412 #> 824 28.3 4 1783 1783-04-02 06:00:00 bone 412 #> 825 23.0 5 1783 1783-05-02 16:00:00 blood 413 #> 826 23.0 5 1783 1783-05-02 16:00:00 bone 413 #> 827 25.2 6 1783 1783-06-02 02:00:01 blood 414 #> 828 25.2 6 1783 1783-06-02 02:00:01 bone 414 #> 829 32.2 7 1783 1783-07-02 12:00:00 blood 415 #> 830 32.2 7 1783 1783-07-02 12:00:00 bone 415 #> 831 20.0 8 1783 1783-08-01 22:00:00 blood 416 #> 832 20.0 8 1783 1783-08-01 22:00:00 bone 416 #> 833 18.0 9 1783 1783-09-01 08:00:01 blood 417 #> 834 18.0 9 1783 1783-09-01 08:00:01 bone 417 #> 835 8.0 10 1783 1783-10-01 18:00:00 blood 418 #> 836 8.0 10 1783 1783-10-01 18:00:00 bone 418 #> 837 15.0 11 1783 1783-11-01 04:00:00 blood 419 #> 838 15.0 11 1783 1783-11-01 04:00:00 bone 419 #> 839 10.5 12 1783 1783-12-01 14:00:01 blood 420 #> 840 10.5 12 1783 1783-12-01 14:00:01 bone 420 #> 841 13.0 1 1784 1784-01-01 00:00:00 blood 421 #> 842 13.0 1 1784 1784-01-01 00:00:00 bone 421 #> 843 8.0 2 1784 1784-01-31 12:00:00 blood 422 #> 844 8.0 2 1784 1784-01-31 12:00:00 bone 422 #> 845 11.0 3 1784 1784-03-02 00:00:01 blood 423 #> 846 11.0 3 1784 1784-03-02 00:00:01 bone 423 #> 847 10.0 4 1784 1784-04-01 12:00:00 blood 424 #> 848 10.0 4 1784 1784-04-01 12:00:00 bone 424 #> 849 6.0 5 1784 1784-05-02 00:00:00 blood 425 #> 850 6.0 5 1784 1784-05-02 00:00:00 bone 425 #> 851 9.0 6 1784 1784-06-01 12:00:01 blood 426 #> 852 9.0 6 1784 1784-06-01 12:00:01 bone 426 #> 853 6.0 7 1784 1784-07-02 00:00:00 blood 427 #> 854 6.0 7 1784 1784-07-02 00:00:00 bone 427 #> 855 10.0 8 1784 1784-08-01 12:00:00 blood 428 #> 856 10.0 8 1784 1784-08-01 12:00:00 bone 428 #> 857 10.0 9 1784 1784-09-01 00:00:01 blood 429 #> 858 10.0 9 1784 1784-09-01 00:00:01 bone 429 #> 859 8.0 10 1784 1784-10-01 12:00:00 blood 430 #> 860 8.0 10 1784 1784-10-01 12:00:00 bone 430 #> 861 17.0 11 1784 1784-11-01 00:00:00 blood 431 #> 862 17.0 11 1784 1784-11-01 00:00:00 bone 431 #> 863 14.0 12 1784 1784-12-01 12:00:01 blood 432 #> 864 14.0 12 1784 1784-12-01 12:00:01 bone 432 #> 865 6.5 1 1785 1785-01-01 00:00:00 blood 433 #> 866 6.5 1 1785 1785-01-01 00:00:00 bone 433 #> 867 8.0 2 1785 1785-01-31 10:00:00 blood 434 #> 868 8.0 2 1785 1785-01-31 10:00:00 bone 434 #> 869 9.0 3 1785 1785-03-02 20:00:01 blood 435 #> 870 9.0 3 1785 1785-03-02 20:00:01 bone 435 #> 871 15.7 4 1785 1785-04-02 06:00:00 blood 436 #> 872 15.7 4 1785 1785-04-02 06:00:00 bone 436 #> 873 20.7 5 1785 1785-05-02 16:00:00 blood 437 #> 874 20.7 5 1785 1785-05-02 16:00:00 bone 437 #> 875 26.3 6 1785 1785-06-02 02:00:01 blood 438 #> 876 26.3 6 1785 1785-06-02 02:00:01 bone 438 #> 877 36.3 7 1785 1785-07-02 12:00:00 blood 439 #> 878 36.3 7 1785 1785-07-02 12:00:00 bone 439 #> 879 20.0 8 1785 1785-08-01 22:00:00 blood 440 #> 880 20.0 8 1785 1785-08-01 22:00:00 bone 440 #> 881 32.0 9 1785 1785-09-01 08:00:01 blood 441 #> 882 32.0 9 1785 1785-09-01 08:00:01 bone 441 #> 883 47.2 10 1785 1785-10-01 18:00:00 blood 442 #> 884 47.2 10 1785 1785-10-01 18:00:00 bone 442 #> 885 40.2 11 1785 1785-11-01 04:00:00 blood 443 #> 886 40.2 11 1785 1785-11-01 04:00:00 bone 443 #> 887 27.3 12 1785 1785-12-01 14:00:01 blood 444 #> 888 27.3 12 1785 1785-12-01 14:00:01 bone 444 #> 889 37.2 1 1786 1786-01-01 00:00:00 blood 445 #> 890 37.2 1 1786 1786-01-01 00:00:00 bone 445 #> 891 47.6 2 1786 1786-01-31 10:00:00 blood 446 #> 892 47.6 2 1786 1786-01-31 10:00:00 bone 446 #> 893 47.7 3 1786 1786-03-02 20:00:01 blood 447 #> 894 47.7 3 1786 1786-03-02 20:00:01 bone 447 #> 895 85.4 4 1786 1786-04-02 06:00:00 blood 448 #> 896 85.4 4 1786 1786-04-02 06:00:00 bone 448 #> 897 92.3 5 1786 1786-05-02 16:00:00 blood 449 #> 898 92.3 5 1786 1786-05-02 16:00:00 bone 449 #> 899 59.0 6 1786 1786-06-02 02:00:01 blood 450 #> 900 59.0 6 1786 1786-06-02 02:00:01 bone 450 #> 901 83.0 7 1786 1786-07-02 12:00:00 blood 451 #> 902 83.0 7 1786 1786-07-02 12:00:00 bone 451 #> 903 89.7 8 1786 1786-08-01 22:00:00 blood 452 #> 904 89.7 8 1786 1786-08-01 22:00:00 bone 452 #> 905 111.5 9 1786 1786-09-01 08:00:01 blood 453 #> 906 111.5 9 1786 1786-09-01 08:00:01 bone 453 #> 907 112.3 10 1786 1786-10-01 18:00:00 blood 454 #> 908 112.3 10 1786 1786-10-01 18:00:00 bone 454 #> 909 116.0 11 1786 1786-11-01 04:00:00 blood 455 #> 910 116.0 11 1786 1786-11-01 04:00:00 bone 455 #> 911 112.7 12 1786 1786-12-01 14:00:01 blood 456 #> 912 112.7 12 1786 1786-12-01 14:00:01 bone 456 #> 913 134.7 1 1787 1787-01-01 00:00:00 blood 457 #> 914 134.7 1 1787 1787-01-01 00:00:00 bone 457 #> 915 106.0 2 1787 1787-01-31 10:00:00 blood 458 #> 916 106.0 2 1787 1787-01-31 10:00:00 bone 458 #> 917 87.4 3 1787 1787-03-02 20:00:01 blood 459 #> 918 87.4 3 1787 1787-03-02 20:00:01 bone 459 #> 919 127.2 4 1787 1787-04-02 06:00:00 blood 460 #> 920 127.2 4 1787 1787-04-02 06:00:00 bone 460 #> 921 134.8 5 1787 1787-05-02 16:00:00 blood 461 #> 922 134.8 5 1787 1787-05-02 16:00:00 bone 461 #> 923 99.2 6 1787 1787-06-02 02:00:01 blood 462 #> 924 99.2 6 1787 1787-06-02 02:00:01 bone 462 #> 925 128.0 7 1787 1787-07-02 12:00:00 blood 463 #> 926 128.0 7 1787 1787-07-02 12:00:00 bone 463 #> 927 137.2 8 1787 1787-08-01 22:00:00 blood 464 #> 928 137.2 8 1787 1787-08-01 22:00:00 bone 464 #> 929 157.3 9 1787 1787-09-01 08:00:01 blood 465 #> 930 157.3 9 1787 1787-09-01 08:00:01 bone 465 #> 931 157.0 10 1787 1787-10-01 18:00:00 blood 466 #> 932 157.0 10 1787 1787-10-01 18:00:00 bone 466 #> 933 141.5 11 1787 1787-11-01 04:00:00 blood 467 #> 934 141.5 11 1787 1787-11-01 04:00:00 bone 467 #> 935 174.0 12 1787 1787-12-01 14:00:01 blood 468 #> 936 174.0 12 1787 1787-12-01 14:00:01 bone 468 #> 937 138.0 1 1788 1788-01-01 00:00:00 blood 469 #> 938 138.0 1 1788 1788-01-01 00:00:00 bone 469 #> 939 129.2 2 1788 1788-01-31 12:00:00 blood 470 #> 940 129.2 2 1788 1788-01-31 12:00:00 bone 470 #> 941 143.3 3 1788 1788-03-02 00:00:01 blood 471 #> 942 143.3 3 1788 1788-03-02 00:00:01 bone 471 #> 943 108.5 4 1788 1788-04-01 12:00:00 blood 472 #> 944 108.5 4 1788 1788-04-01 12:00:00 bone 472 #> 945 113.0 5 1788 1788-05-02 00:00:00 blood 473 #> 946 113.0 5 1788 1788-05-02 00:00:00 bone 473 #> 947 154.2 6 1788 1788-06-01 12:00:01 blood 474 #> 948 154.2 6 1788 1788-06-01 12:00:01 bone 474 #> 949 141.5 7 1788 1788-07-02 00:00:00 blood 475 #> 950 141.5 7 1788 1788-07-02 00:00:00 bone 475 #> 951 136.0 8 1788 1788-08-01 12:00:00 blood 476 #> 952 136.0 8 1788 1788-08-01 12:00:00 bone 476 #> 953 141.0 9 1788 1788-09-01 00:00:01 blood 477 #> 954 141.0 9 1788 1788-09-01 00:00:01 bone 477 #> 955 142.0 10 1788 1788-10-01 12:00:00 blood 478 #> 956 142.0 10 1788 1788-10-01 12:00:00 bone 478 #> 957 94.7 11 1788 1788-11-01 00:00:00 blood 479 #> 958 94.7 11 1788 1788-11-01 00:00:00 bone 479 #> 959 129.5 12 1788 1788-12-01 12:00:01 blood 480 #> 960 129.5 12 1788 1788-12-01 12:00:01 bone 480 #> 961 114.0 1 1789 1789-01-01 00:00:00 blood 481 #> 962 114.0 1 1789 1789-01-01 00:00:00 bone 481 #> 963 125.3 2 1789 1789-01-31 10:00:00 blood 482 #> 964 125.3 2 1789 1789-01-31 10:00:00 bone 482 #> 965 120.0 3 1789 1789-03-02 20:00:01 blood 483 #> 966 120.0 3 1789 1789-03-02 20:00:01 bone 483 #> 967 123.3 4 1789 1789-04-02 06:00:00 blood 484 #> 968 123.3 4 1789 1789-04-02 06:00:00 bone 484 #> 969 123.5 5 1789 1789-05-02 16:00:00 blood 485 #> 970 123.5 5 1789 1789-05-02 16:00:00 bone 485 #> 971 120.0 6 1789 1789-06-02 02:00:01 blood 486 #> 972 120.0 6 1789 1789-06-02 02:00:01 bone 486 #> 973 117.0 7 1789 1789-07-02 12:00:00 blood 487 #> 974 117.0 7 1789 1789-07-02 12:00:00 bone 487 #> 975 103.0 8 1789 1789-08-01 22:00:00 blood 488 #> 976 103.0 8 1789 1789-08-01 22:00:00 bone 488 #> 977 112.0 9 1789 1789-09-01 08:00:01 blood 489 #> 978 112.0 9 1789 1789-09-01 08:00:01 bone 489 #> 979 89.7 10 1789 1789-10-01 18:00:00 blood 490 #> 980 89.7 10 1789 1789-10-01 18:00:00 bone 490 #> 981 134.0 11 1789 1789-11-01 04:00:00 blood 491 #> 982 134.0 11 1789 1789-11-01 04:00:00 bone 491 #> 983 135.5 12 1789 1789-12-01 14:00:01 blood 492 #> 984 135.5 12 1789 1789-12-01 14:00:01 bone 492 #> 985 103.0 1 1790 1790-01-01 00:00:00 blood 493 #> 986 103.0 1 1790 1790-01-01 00:00:00 bone 493 #> 987 127.5 2 1790 1790-01-31 10:00:00 blood 494 #> 988 127.5 2 1790 1790-01-31 10:00:00 bone 494 #> 989 96.3 3 1790 1790-03-02 20:00:01 blood 495 #> 990 96.3 3 1790 1790-03-02 20:00:01 bone 495 #> 991 94.0 4 1790 1790-04-02 06:00:00 blood 496 #> 992 94.0 4 1790 1790-04-02 06:00:00 bone 496 #> 993 93.0 5 1790 1790-05-02 16:00:00 blood 497 #> 994 93.0 5 1790 1790-05-02 16:00:00 bone 497 #> 995 91.0 6 1790 1790-06-02 02:00:01 blood 498 #> 996 91.0 6 1790 1790-06-02 02:00:01 bone 498 #> 997 69.3 7 1790 1790-07-02 12:00:00 blood 499 #> 998 69.3 7 1790 1790-07-02 12:00:00 bone 499 #> 999 87.0 8 1790 1790-08-01 22:00:00 blood 500 #> 1000 87.0 8 1790 1790-08-01 22:00:00 bone 500 #> 1001 77.3 9 1790 1790-09-01 08:00:01 blood 501 #> 1002 77.3 9 1790 1790-09-01 08:00:01 bone 501 #> 1003 84.3 10 1790 1790-10-01 18:00:00 blood 502 #> 1004 84.3 10 1790 1790-10-01 18:00:00 bone 502 #> 1005 82.0 11 1790 1790-11-01 04:00:00 blood 503 #> 1006 82.0 11 1790 1790-11-01 04:00:00 bone 503 #> 1007 74.0 12 1790 1790-12-01 14:00:01 blood 504 #> 1008 74.0 12 1790 1790-12-01 14:00:01 bone 504 #> 1009 72.7 1 1791 1791-01-01 00:00:00 blood 505 #> 1010 72.7 1 1791 1791-01-01 00:00:00 bone 505 #> 1011 62.0 2 1791 1791-01-31 10:00:00 blood 506 #> 1012 62.0 2 1791 1791-01-31 10:00:00 bone 506 #> 1013 74.0 3 1791 1791-03-02 20:00:01 blood 507 #> 1014 74.0 3 1791 1791-03-02 20:00:01 bone 507 #> 1015 77.2 4 1791 1791-04-02 06:00:00 blood 508 #> 1016 77.2 4 1791 1791-04-02 06:00:00 bone 508 #> 1017 73.7 5 1791 1791-05-02 16:00:00 blood 509 #> 1018 73.7 5 1791 1791-05-02 16:00:00 bone 509 #> 1019 64.2 6 1791 1791-06-02 02:00:01 blood 510 #> 1020 64.2 6 1791 1791-06-02 02:00:01 bone 510 #> 1021 71.0 7 1791 1791-07-02 12:00:00 blood 511 #> 1022 71.0 7 1791 1791-07-02 12:00:00 bone 511 #> 1023 43.0 8 1791 1791-08-01 22:00:00 blood 512 #> 1024 43.0 8 1791 1791-08-01 22:00:00 bone 512 #> 1025 66.5 9 1791 1791-09-01 08:00:01 blood 513 #> 1026 66.5 9 1791 1791-09-01 08:00:01 bone 513 #> 1027 61.7 10 1791 1791-10-01 18:00:00 blood 514 #> 1028 61.7 10 1791 1791-10-01 18:00:00 bone 514 #> 1029 67.0 11 1791 1791-11-01 04:00:00 blood 515 #> 1030 67.0 11 1791 1791-11-01 04:00:00 bone 515 #> 1031 66.0 12 1791 1791-12-01 14:00:01 blood 516 #> 1032 66.0 12 1791 1791-12-01 14:00:01 bone 516 #> 1033 58.0 1 1792 1792-01-01 00:00:00 blood 517 #> 1034 58.0 1 1792 1792-01-01 00:00:00 bone 517 #> 1035 64.0 2 1792 1792-01-31 12:00:00 blood 518 #> 1036 64.0 2 1792 1792-01-31 12:00:00 bone 518 #> 1037 63.0 3 1792 1792-03-02 00:00:01 blood 519 #> 1038 63.0 3 1792 1792-03-02 00:00:01 bone 519 #> 1039 75.7 4 1792 1792-04-01 12:00:00 blood 520 #> 1040 75.7 4 1792 1792-04-01 12:00:00 bone 520 #> 1041 62.0 5 1792 1792-05-02 00:00:00 blood 521 #> 1042 62.0 5 1792 1792-05-02 00:00:00 bone 521 #> 1043 61.0 6 1792 1792-06-01 12:00:01 blood 522 #> 1044 61.0 6 1792 1792-06-01 12:00:01 bone 522 #> 1045 45.8 7 1792 1792-07-02 00:00:00 blood 523 #> 1046 45.8 7 1792 1792-07-02 00:00:00 bone 523 #> 1047 60.0 8 1792 1792-08-01 12:00:00 blood 524 #> 1048 60.0 8 1792 1792-08-01 12:00:00 bone 524 #> 1049 59.0 9 1792 1792-09-01 00:00:01 blood 525 #> 1050 59.0 9 1792 1792-09-01 00:00:01 bone 525 #> 1051 59.0 10 1792 1792-10-01 12:00:00 blood 526 #> 1052 59.0 10 1792 1792-10-01 12:00:00 bone 526 #> 1053 57.0 11 1792 1792-11-01 00:00:00 blood 527 #> 1054 57.0 11 1792 1792-11-01 00:00:00 bone 527 #> 1055 56.0 12 1792 1792-12-01 12:00:01 blood 528 #> 1056 56.0 12 1792 1792-12-01 12:00:01 bone 528 #> 1057 56.0 1 1793 1793-01-01 00:00:00 blood 529 #> 1058 56.0 1 1793 1793-01-01 00:00:00 bone 529 #> 1059 55.0 2 1793 1793-01-31 10:00:00 blood 530 #> 1060 55.0 2 1793 1793-01-31 10:00:00 bone 530 #> 1061 55.5 3 1793 1793-03-02 20:00:01 blood 531 #> 1062 55.5 3 1793 1793-03-02 20:00:01 bone 531 #> 1063 53.0 4 1793 1793-04-02 06:00:00 blood 532 #> 1064 53.0 4 1793 1793-04-02 06:00:00 bone 532 #> 1065 52.3 5 1793 1793-05-02 16:00:00 blood 533 #> 1066 52.3 5 1793 1793-05-02 16:00:00 bone 533 #> 1067 51.0 6 1793 1793-06-02 02:00:01 blood 534 #> 1068 51.0 6 1793 1793-06-02 02:00:01 bone 534 #> 1069 50.0 7 1793 1793-07-02 12:00:00 blood 535 #> 1070 50.0 7 1793 1793-07-02 12:00:00 bone 535 #> 1071 29.3 8 1793 1793-08-01 22:00:00 blood 536 #> 1072 29.3 8 1793 1793-08-01 22:00:00 bone 536 #> 1073 24.0 9 1793 1793-09-01 08:00:01 blood 537 #> 1074 24.0 9 1793 1793-09-01 08:00:01 bone 537 #> 1075 47.0 10 1793 1793-10-01 18:00:00 blood 538 #> 1076 47.0 10 1793 1793-10-01 18:00:00 bone 538 #> 1077 44.0 11 1793 1793-11-01 04:00:00 blood 539 #> 1078 44.0 11 1793 1793-11-01 04:00:00 bone 539 #> 1079 45.7 12 1793 1793-12-01 14:00:01 blood 540 #> 1080 45.7 12 1793 1793-12-01 14:00:01 bone 540 #> 1081 45.0 1 1794 1794-01-01 00:00:00 blood 541 #> 1082 45.0 1 1794 1794-01-01 00:00:00 bone 541 #> 1083 44.0 2 1794 1794-01-31 10:00:00 blood 542 #> 1084 44.0 2 1794 1794-01-31 10:00:00 bone 542 #> 1085 38.0 3 1794 1794-03-02 20:00:01 blood 543 #> 1086 38.0 3 1794 1794-03-02 20:00:01 bone 543 #> 1087 28.4 4 1794 1794-04-02 06:00:00 blood 544 #> 1088 28.4 4 1794 1794-04-02 06:00:00 bone 544 #> 1089 55.7 5 1794 1794-05-02 16:00:00 blood 545 #> 1090 55.7 5 1794 1794-05-02 16:00:00 bone 545 #> 1091 41.5 6 1794 1794-06-02 02:00:01 blood 546 #> 1092 41.5 6 1794 1794-06-02 02:00:01 bone 546 #> 1093 41.0 7 1794 1794-07-02 12:00:00 blood 547 #> 1094 41.0 7 1794 1794-07-02 12:00:00 bone 547 #> 1095 40.0 8 1794 1794-08-01 22:00:00 blood 548 #> 1096 40.0 8 1794 1794-08-01 22:00:00 bone 548 #> 1097 11.1 9 1794 1794-09-01 08:00:01 blood 549 #> 1098 11.1 9 1794 1794-09-01 08:00:01 bone 549 #> 1099 28.5 10 1794 1794-10-01 18:00:00 blood 550 #> 1100 28.5 10 1794 1794-10-01 18:00:00 bone 550 #> 1101 67.4 11 1794 1794-11-01 04:00:00 blood 551 #> 1102 67.4 11 1794 1794-11-01 04:00:00 bone 551 #> 1103 51.4 12 1794 1794-12-01 14:00:01 blood 552 #> 1104 51.4 12 1794 1794-12-01 14:00:01 bone 552 #> 1105 21.4 1 1795 1795-01-01 00:00:00 blood 553 #> 1106 21.4 1 1795 1795-01-01 00:00:00 bone 553 #> 1107 39.9 2 1795 1795-01-31 10:00:00 blood 554 #> 1108 39.9 2 1795 1795-01-31 10:00:00 bone 554 #> 1109 12.6 3 1795 1795-03-02 20:00:01 blood 555 #> 1110 12.6 3 1795 1795-03-02 20:00:01 bone 555 #> 1111 18.6 4 1795 1795-04-02 06:00:00 blood 556 #> 1112 18.6 4 1795 1795-04-02 06:00:00 bone 556 #> 1113 31.0 5 1795 1795-05-02 16:00:00 blood 557 #> 1114 31.0 5 1795 1795-05-02 16:00:00 bone 557 #> 1115 17.1 6 1795 1795-06-02 02:00:01 blood 558 #> 1116 17.1 6 1795 1795-06-02 02:00:01 bone 558 #> 1117 12.9 7 1795 1795-07-02 12:00:00 blood 559 #> 1118 12.9 7 1795 1795-07-02 12:00:00 bone 559 #> 1119 25.7 8 1795 1795-08-01 22:00:00 blood 560 #> 1120 25.7 8 1795 1795-08-01 22:00:00 bone 560 #> 1121 13.5 9 1795 1795-09-01 08:00:01 blood 561 #> 1122 13.5 9 1795 1795-09-01 08:00:01 bone 561 #> 1123 19.5 10 1795 1795-10-01 18:00:00 blood 562 #> 1124 19.5 10 1795 1795-10-01 18:00:00 bone 562 #> 1125 25.0 11 1795 1795-11-01 04:00:00 blood 563 #> 1126 25.0 11 1795 1795-11-01 04:00:00 bone 563 #> 1127 18.0 12 1795 1795-12-01 14:00:01 blood 564 #> 1128 18.0 12 1795 1795-12-01 14:00:01 bone 564 #> 1129 22.0 1 1796 1796-01-01 00:00:00 blood 565 #> 1130 22.0 1 1796 1796-01-01 00:00:00 bone 565 #> 1131 23.8 2 1796 1796-01-31 12:00:00 blood 566 #> 1132 23.8 2 1796 1796-01-31 12:00:00 bone 566 #> 1133 15.7 3 1796 1796-03-02 00:00:01 blood 567 #> 1134 15.7 3 1796 1796-03-02 00:00:01 bone 567 #> 1135 31.7 4 1796 1796-04-01 12:00:00 blood 568 #> 1136 31.7 4 1796 1796-04-01 12:00:00 bone 568 #> 1137 21.0 5 1796 1796-05-02 00:00:00 blood 569 #> 1138 21.0 5 1796 1796-05-02 00:00:00 bone 569 #> 1139 6.7 6 1796 1796-06-01 12:00:01 blood 570 #> 1140 6.7 6 1796 1796-06-01 12:00:01 bone 570 #> 1141 26.9 7 1796 1796-07-02 00:00:00 blood 571 #> 1142 26.9 7 1796 1796-07-02 00:00:00 bone 571 #> 1143 1.5 8 1796 1796-08-01 12:00:00 blood 572 #> 1144 1.5 8 1796 1796-08-01 12:00:00 bone 572 #> 1145 18.4 9 1796 1796-09-01 00:00:01 blood 573 #> 1146 18.4 9 1796 1796-09-01 00:00:01 bone 573 #> 1147 11.0 10 1796 1796-10-01 12:00:00 blood 574 #> 1148 11.0 10 1796 1796-10-01 12:00:00 bone 574 #> 1149 8.4 11 1796 1796-11-01 00:00:00 blood 575 #> 1150 8.4 11 1796 1796-11-01 00:00:00 bone 575 #> 1151 5.1 12 1796 1796-12-01 12:00:01 blood 576 #> 1152 5.1 12 1796 1796-12-01 12:00:01 bone 576 #> 1153 14.4 1 1797 1797-01-01 00:00:00 blood 577 #> 1154 14.4 1 1797 1797-01-01 00:00:00 bone 577 #> 1155 4.2 2 1797 1797-01-31 10:00:00 blood 578 #> 1156 4.2 2 1797 1797-01-31 10:00:00 bone 578 #> 1157 4.0 3 1797 1797-03-02 20:00:01 blood 579 #> 1158 4.0 3 1797 1797-03-02 20:00:01 bone 579 #> 1159 4.0 4 1797 1797-04-02 06:00:00 blood 580 #> 1160 4.0 4 1797 1797-04-02 06:00:00 bone 580 #> 1161 7.3 5 1797 1797-05-02 16:00:00 blood 581 #> 1162 7.3 5 1797 1797-05-02 16:00:00 bone 581 #> 1163 11.1 6 1797 1797-06-02 02:00:01 blood 582 #> 1164 11.1 6 1797 1797-06-02 02:00:01 bone 582 #> 1165 4.3 7 1797 1797-07-02 12:00:00 blood 583 #> 1166 4.3 7 1797 1797-07-02 12:00:00 bone 583 #> 1167 6.0 8 1797 1797-08-01 22:00:00 blood 584 #> 1168 6.0 8 1797 1797-08-01 22:00:00 bone 584 #> 1169 5.7 9 1797 1797-09-01 08:00:01 blood 585 #> 1170 5.7 9 1797 1797-09-01 08:00:01 bone 585 #> 1171 6.9 10 1797 1797-10-01 18:00:00 blood 586 #> 1172 6.9 10 1797 1797-10-01 18:00:00 bone 586 #> 1173 5.8 11 1797 1797-11-01 04:00:00 blood 587 #> 1174 5.8 11 1797 1797-11-01 04:00:00 bone 587 #> 1175 3.0 12 1797 1797-12-01 14:00:01 blood 588 #> 1176 3.0 12 1797 1797-12-01 14:00:01 bone 588 #> 1177 2.0 1 1798 1798-01-01 00:00:00 blood 589 #> 1178 2.0 1 1798 1798-01-01 00:00:00 bone 589 #> 1179 4.0 2 1798 1798-01-31 10:00:00 blood 590 #> 1180 4.0 2 1798 1798-01-31 10:00:00 bone 590 #> 1181 12.4 3 1798 1798-03-02 20:00:01 blood 591 #> 1182 12.4 3 1798 1798-03-02 20:00:01 bone 591 #> 1183 1.1 4 1798 1798-04-02 06:00:00 blood 592 #> 1184 1.1 4 1798 1798-04-02 06:00:00 bone 592 #> 1185 0.0 5 1798 1798-05-02 16:00:00 blood 593 #> 1186 0.0 5 1798 1798-05-02 16:00:00 bone 593 #> 1187 0.0 6 1798 1798-06-02 02:00:01 blood 594 #> 1188 0.0 6 1798 1798-06-02 02:00:01 bone 594 #> 1189 0.0 7 1798 1798-07-02 12:00:00 blood 595 #> 1190 0.0 7 1798 1798-07-02 12:00:00 bone 595 #> 1191 3.0 8 1798 1798-08-01 22:00:00 blood 596 #> 1192 3.0 8 1798 1798-08-01 22:00:00 bone 596 #> 1193 2.4 9 1798 1798-09-01 08:00:01 blood 597 #> 1194 2.4 9 1798 1798-09-01 08:00:01 bone 597 #> 1195 1.5 10 1798 1798-10-01 18:00:00 blood 598 #> 1196 1.5 10 1798 1798-10-01 18:00:00 bone 598 #> 1197 12.5 11 1798 1798-11-01 04:00:00 blood 599 #> 1198 12.5 11 1798 1798-11-01 04:00:00 bone 599 #> 1199 9.9 12 1798 1798-12-01 14:00:01 blood 600 #> 1200 9.9 12 1798 1798-12-01 14:00:01 bone 600 #> 1201 1.6 1 1799 1799-01-01 00:00:00 blood 601 #> 1202 1.6 1 1799 1799-01-01 00:00:00 bone 601 #> 1203 12.6 2 1799 1799-01-31 10:00:00 blood 602 #> 1204 12.6 2 1799 1799-01-31 10:00:00 bone 602 #> 1205 21.7 3 1799 1799-03-02 20:00:01 blood 603 #> 1206 21.7 3 1799 1799-03-02 20:00:01 bone 603 #> 1207 8.4 4 1799 1799-04-02 06:00:00 blood 604 #> 1208 8.4 4 1799 1799-04-02 06:00:00 bone 604 #> 1209 8.2 5 1799 1799-05-02 16:00:00 blood 605 #> 1210 8.2 5 1799 1799-05-02 16:00:00 bone 605 #> 1211 10.6 6 1799 1799-06-02 02:00:01 blood 606 #> 1212 10.6 6 1799 1799-06-02 02:00:01 bone 606 #> 1213 2.1 7 1799 1799-07-02 12:00:00 blood 607 #> 1214 2.1 7 1799 1799-07-02 12:00:00 bone 607 #> 1215 0.0 8 1799 1799-08-01 22:00:00 blood 608 #> 1216 0.0 8 1799 1799-08-01 22:00:00 bone 608 #> 1217 0.0 9 1799 1799-09-01 08:00:01 blood 609 #> 1218 0.0 9 1799 1799-09-01 08:00:01 bone 609 #> 1219 4.6 10 1799 1799-10-01 18:00:00 blood 610 #> 1220 4.6 10 1799 1799-10-01 18:00:00 bone 610 #> 1221 2.7 11 1799 1799-11-01 04:00:00 blood 611 #> 1222 2.7 11 1799 1799-11-01 04:00:00 bone 611 #> 1223 8.6 12 1799 1799-12-01 14:00:01 blood 612 #> 1224 8.6 12 1799 1799-12-01 14:00:01 bone 612 #> 1225 6.9 1 1800 1800-01-01 00:00:00 blood 613 #> 1226 6.9 1 1800 1800-01-01 00:00:00 bone 613 #> 1227 9.3 2 1800 1800-01-31 10:00:00 blood 614 #> 1228 9.3 2 1800 1800-01-31 10:00:00 bone 614 #> 1229 13.9 3 1800 1800-03-02 20:00:01 blood 615 #> 1230 13.9 3 1800 1800-03-02 20:00:01 bone 615 #> 1231 0.0 4 1800 1800-04-02 06:00:00 blood 616 #> 1232 0.0 4 1800 1800-04-02 06:00:00 bone 616 #> 1233 5.0 5 1800 1800-05-02 16:00:00 blood 617 #> 1234 5.0 5 1800 1800-05-02 16:00:00 bone 617 #> 1235 23.7 6 1800 1800-06-02 02:00:01 blood 618 #> 1236 23.7 6 1800 1800-06-02 02:00:01 bone 618 #> 1237 21.0 7 1800 1800-07-02 12:00:00 blood 619 #> 1238 21.0 7 1800 1800-07-02 12:00:00 bone 619 #> 1239 19.5 8 1800 1800-08-01 22:00:00 blood 620 #> 1240 19.5 8 1800 1800-08-01 22:00:00 bone 620 #> 1241 11.5 9 1800 1800-09-01 08:00:01 blood 621 #> 1242 11.5 9 1800 1800-09-01 08:00:01 bone 621 #> 1243 12.3 10 1800 1800-10-01 18:00:00 blood 622 #> 1244 12.3 10 1800 1800-10-01 18:00:00 bone 622 #> 1245 10.5 11 1800 1800-11-01 04:00:00 blood 623 #> 1246 10.5 11 1800 1800-11-01 04:00:00 bone 623 #> 1247 40.1 12 1800 1800-12-01 14:00:01 blood 624 #> 1248 40.1 12 1800 1800-12-01 14:00:01 bone 624 #> 1249 27.0 1 1801 1801-01-01 00:00:00 blood 625 #> 1250 27.0 1 1801 1801-01-01 00:00:00 bone 625 #> 1251 29.0 2 1801 1801-01-31 10:00:00 blood 626 #> 1252 29.0 2 1801 1801-01-31 10:00:00 bone 626 #> 1253 30.0 3 1801 1801-03-02 20:00:01 blood 627 #> 1254 30.0 3 1801 1801-03-02 20:00:01 bone 627 #> 1255 31.0 4 1801 1801-04-02 06:00:00 blood 628 #> 1256 31.0 4 1801 1801-04-02 06:00:00 bone 628 #> 1257 32.0 5 1801 1801-05-02 16:00:00 blood 629 #> 1258 32.0 5 1801 1801-05-02 16:00:00 bone 629 #> 1259 31.2 6 1801 1801-06-02 02:00:01 blood 630 #> 1260 31.2 6 1801 1801-06-02 02:00:01 bone 630 #> 1261 35.0 7 1801 1801-07-02 12:00:00 blood 631 #> 1262 35.0 7 1801 1801-07-02 12:00:00 bone 631 #> 1263 38.7 8 1801 1801-08-01 22:00:00 blood 632 #> 1264 38.7 8 1801 1801-08-01 22:00:00 bone 632 #> 1265 33.5 9 1801 1801-09-01 08:00:01 blood 633 #> 1266 33.5 9 1801 1801-09-01 08:00:01 bone 633 #> 1267 32.6 10 1801 1801-10-01 18:00:00 blood 634 #> 1268 32.6 10 1801 1801-10-01 18:00:00 bone 634 #> 1269 39.8 11 1801 1801-11-01 04:00:00 blood 635 #> 1270 39.8 11 1801 1801-11-01 04:00:00 bone 635 #> 1271 48.2 12 1801 1801-12-01 14:00:01 blood 636 #> 1272 48.2 12 1801 1801-12-01 14:00:01 bone 636 #> 1273 47.8 1 1802 1802-01-01 00:00:00 blood 637 #> 1274 47.8 1 1802 1802-01-01 00:00:00 bone 637 #> 1275 47.0 2 1802 1802-01-31 10:00:00 blood 638 #> 1276 47.0 2 1802 1802-01-31 10:00:00 bone 638 #> 1277 40.8 3 1802 1802-03-02 20:00:01 blood 639 #> 1278 40.8 3 1802 1802-03-02 20:00:01 bone 639 #> 1279 42.0 4 1802 1802-04-02 06:00:00 blood 640 #> 1280 42.0 4 1802 1802-04-02 06:00:00 bone 640 #> 1281 44.0 5 1802 1802-05-02 16:00:00 blood 641 #> 1282 44.0 5 1802 1802-05-02 16:00:00 bone 641 #> 1283 46.0 6 1802 1802-06-02 02:00:01 blood 642 #> 1284 46.0 6 1802 1802-06-02 02:00:01 bone 642 #> 1285 48.0 7 1802 1802-07-02 12:00:00 blood 643 #> 1286 48.0 7 1802 1802-07-02 12:00:00 bone 643 #> 1287 50.0 8 1802 1802-08-01 22:00:00 blood 644 #> 1288 50.0 8 1802 1802-08-01 22:00:00 bone 644 #> 1289 51.8 9 1802 1802-09-01 08:00:01 blood 645 #> 1290 51.8 9 1802 1802-09-01 08:00:01 bone 645 #> 1291 38.5 10 1802 1802-10-01 18:00:00 blood 646 #> 1292 38.5 10 1802 1802-10-01 18:00:00 bone 646 #> 1293 34.5 11 1802 1802-11-01 04:00:00 blood 647 #> 1294 34.5 11 1802 1802-11-01 04:00:00 bone 647 #> 1295 50.0 12 1802 1802-12-01 14:00:01 blood 648 #> 1296 50.0 12 1802 1802-12-01 14:00:01 bone 648 #> 1297 50.0 1 1803 1803-01-01 00:00:00 blood 649 #> 1298 50.0 1 1803 1803-01-01 00:00:00 bone 649 #> 1299 50.8 2 1803 1803-01-31 10:00:00 blood 650 #> 1300 50.8 2 1803 1803-01-31 10:00:00 bone 650 #> 1301 29.5 3 1803 1803-03-02 20:00:01 blood 651 #> 1302 29.5 3 1803 1803-03-02 20:00:01 bone 651 #> 1303 25.0 4 1803 1803-04-02 06:00:00 blood 652 #> 1304 25.0 4 1803 1803-04-02 06:00:00 bone 652 #> 1305 44.3 5 1803 1803-05-02 16:00:00 blood 653 #> 1306 44.3 5 1803 1803-05-02 16:00:00 bone 653 #> 1307 36.0 6 1803 1803-06-02 02:00:01 blood 654 #> 1308 36.0 6 1803 1803-06-02 02:00:01 bone 654 #> 1309 48.3 7 1803 1803-07-02 12:00:00 blood 655 #> 1310 48.3 7 1803 1803-07-02 12:00:00 bone 655 #> 1311 34.1 8 1803 1803-08-01 22:00:00 blood 656 #> 1312 34.1 8 1803 1803-08-01 22:00:00 bone 656 #> 1313 45.3 9 1803 1803-09-01 08:00:01 blood 657 #> 1314 45.3 9 1803 1803-09-01 08:00:01 bone 657 #> 1315 54.3 10 1803 1803-10-01 18:00:00 blood 658 #> 1316 54.3 10 1803 1803-10-01 18:00:00 bone 658 #> 1317 51.0 11 1803 1803-11-01 04:00:00 blood 659 #> 1318 51.0 11 1803 1803-11-01 04:00:00 bone 659 #> 1319 48.0 12 1803 1803-12-01 14:00:01 blood 660 #> 1320 48.0 12 1803 1803-12-01 14:00:01 bone 660 #> 1321 45.3 1 1804 1804-01-01 00:00:00 blood 661 #> 1322 45.3 1 1804 1804-01-01 00:00:00 bone 661 #> 1323 48.3 2 1804 1804-01-31 12:00:00 blood 662 #> 1324 48.3 2 1804 1804-01-31 12:00:00 bone 662 #> 1325 48.0 3 1804 1804-03-02 00:00:01 blood 663 #> 1326 48.0 3 1804 1804-03-02 00:00:01 bone 663 #> 1327 50.6 4 1804 1804-04-01 12:00:00 blood 664 #> 1328 50.6 4 1804 1804-04-01 12:00:00 bone 664 #> 1329 33.4 5 1804 1804-05-02 00:00:00 blood 665 #> 1330 33.4 5 1804 1804-05-02 00:00:00 bone 665 #> 1331 34.8 6 1804 1804-06-01 12:00:01 blood 666 #> 1332 34.8 6 1804 1804-06-01 12:00:01 bone 666 #> 1333 29.8 7 1804 1804-07-02 00:00:00 blood 667 #> 1334 29.8 7 1804 1804-07-02 00:00:00 bone 667 #> 1335 43.1 8 1804 1804-08-01 12:00:00 blood 668 #> 1336 43.1 8 1804 1804-08-01 12:00:00 bone 668 #> 1337 53.0 9 1804 1804-09-01 00:00:01 blood 669 #> 1338 53.0 9 1804 1804-09-01 00:00:01 bone 669 #> 1339 62.3 10 1804 1804-10-01 12:00:00 blood 670 #> 1340 62.3 10 1804 1804-10-01 12:00:00 bone 670 #> 1341 61.0 11 1804 1804-11-01 00:00:00 blood 671 #> 1342 61.0 11 1804 1804-11-01 00:00:00 bone 671 #> 1343 60.0 12 1804 1804-12-01 12:00:01 blood 672 #> 1344 60.0 12 1804 1804-12-01 12:00:01 bone 672 #> 1345 61.0 1 1805 1805-01-01 00:00:00 blood 673 #> 1346 61.0 1 1805 1805-01-01 00:00:00 bone 673 #> 1347 44.1 2 1805 1805-01-31 10:00:00 blood 674 #> 1348 44.1 2 1805 1805-01-31 10:00:00 bone 674 #> 1349 51.4 3 1805 1805-03-02 20:00:01 blood 675 #> 1350 51.4 3 1805 1805-03-02 20:00:01 bone 675 #> 1351 37.5 4 1805 1805-04-02 06:00:00 blood 676 #> 1352 37.5 4 1805 1805-04-02 06:00:00 bone 676 #> 1353 39.0 5 1805 1805-05-02 16:00:00 blood 677 #> 1354 39.0 5 1805 1805-05-02 16:00:00 bone 677 #> 1355 40.5 6 1805 1805-06-02 02:00:01 blood 678 #> 1356 40.5 6 1805 1805-06-02 02:00:01 bone 678 #> 1357 37.6 7 1805 1805-07-02 12:00:00 blood 679 #> 1358 37.6 7 1805 1805-07-02 12:00:00 bone 679 #> 1359 42.7 8 1805 1805-08-01 22:00:00 blood 680 #> 1360 42.7 8 1805 1805-08-01 22:00:00 bone 680 #> 1361 44.4 9 1805 1805-09-01 08:00:01 blood 681 #> 1362 44.4 9 1805 1805-09-01 08:00:01 bone 681 #> 1363 29.4 10 1805 1805-10-01 18:00:00 blood 682 #> 1364 29.4 10 1805 1805-10-01 18:00:00 bone 682 #> 1365 41.0 11 1805 1805-11-01 04:00:00 blood 683 #> 1366 41.0 11 1805 1805-11-01 04:00:00 bone 683 #> 1367 38.3 12 1805 1805-12-01 14:00:01 blood 684 #> 1368 38.3 12 1805 1805-12-01 14:00:01 bone 684 #> 1369 39.0 1 1806 1806-01-01 00:00:00 blood 685 #> 1370 39.0 1 1806 1806-01-01 00:00:00 bone 685 #> 1371 29.6 2 1806 1806-01-31 10:00:00 blood 686 #> 1372 29.6 2 1806 1806-01-31 10:00:00 bone 686 #> 1373 32.7 3 1806 1806-03-02 20:00:01 blood 687 #> 1374 32.7 3 1806 1806-03-02 20:00:01 bone 687 #> 1375 27.7 4 1806 1806-04-02 06:00:00 blood 688 #> 1376 27.7 4 1806 1806-04-02 06:00:00 bone 688 #> 1377 26.4 5 1806 1806-05-02 16:00:00 blood 689 #> 1378 26.4 5 1806 1806-05-02 16:00:00 bone 689 #> 1379 25.6 6 1806 1806-06-02 02:00:01 blood 690 #> 1380 25.6 6 1806 1806-06-02 02:00:01 bone 690 #> 1381 30.0 7 1806 1806-07-02 12:00:00 blood 691 #> 1382 30.0 7 1806 1806-07-02 12:00:00 bone 691 #> 1383 26.3 8 1806 1806-08-01 22:00:00 blood 692 #> 1384 26.3 8 1806 1806-08-01 22:00:00 bone 692 #> 1385 24.0 9 1806 1806-09-01 08:00:01 blood 693 #> 1386 24.0 9 1806 1806-09-01 08:00:01 bone 693 #> 1387 27.0 10 1806 1806-10-01 18:00:00 blood 694 #> 1388 27.0 10 1806 1806-10-01 18:00:00 bone 694 #> 1389 25.0 11 1806 1806-11-01 04:00:00 blood 695 #> 1390 25.0 11 1806 1806-11-01 04:00:00 bone 695 #> 1391 24.0 12 1806 1806-12-01 14:00:01 blood 696 #> 1392 24.0 12 1806 1806-12-01 14:00:01 bone 696 #> 1393 12.0 1 1807 1807-01-01 00:00:00 blood 697 #> 1394 12.0 1 1807 1807-01-01 00:00:00 bone 697 #> 1395 12.2 2 1807 1807-01-31 10:00:00 blood 698 #> 1396 12.2 2 1807 1807-01-31 10:00:00 bone 698 #> 1397 9.6 3 1807 1807-03-02 20:00:01 blood 699 #> 1398 9.6 3 1807 1807-03-02 20:00:01 bone 699 #> 1399 23.8 4 1807 1807-04-02 06:00:00 blood 700 #> 1400 23.8 4 1807 1807-04-02 06:00:00 bone 700 #> 1401 10.0 5 1807 1807-05-02 16:00:00 blood 701 #> 1402 10.0 5 1807 1807-05-02 16:00:00 bone 701 #> 1403 12.0 6 1807 1807-06-02 02:00:01 blood 702 #> 1404 12.0 6 1807 1807-06-02 02:00:01 bone 702 #> 1405 12.7 7 1807 1807-07-02 12:00:00 blood 703 #> 1406 12.7 7 1807 1807-07-02 12:00:00 bone 703 #> 1407 12.0 8 1807 1807-08-01 22:00:00 blood 704 #> 1408 12.0 8 1807 1807-08-01 22:00:00 bone 704 #> 1409 5.7 9 1807 1807-09-01 08:00:01 blood 705 #> 1410 5.7 9 1807 1807-09-01 08:00:01 bone 705 #> 1411 8.0 10 1807 1807-10-01 18:00:00 blood 706 #> 1412 8.0 10 1807 1807-10-01 18:00:00 bone 706 #> 1413 2.6 11 1807 1807-11-01 04:00:00 blood 707 #> 1414 2.6 11 1807 1807-11-01 04:00:00 bone 707 #> 1415 0.0 12 1807 1807-12-01 14:00:01 blood 708 #> 1416 0.0 12 1807 1807-12-01 14:00:01 bone 708 #> 1417 0.0 1 1808 1808-01-01 00:00:00 blood 709 #> 1418 0.0 1 1808 1808-01-01 00:00:00 bone 709 #> 1419 4.5 2 1808 1808-01-31 12:00:00 blood 710 #> 1420 4.5 2 1808 1808-01-31 12:00:00 bone 710 #> 1421 0.0 3 1808 1808-03-02 00:00:01 blood 711 #> 1422 0.0 3 1808 1808-03-02 00:00:01 bone 711 #> 1423 12.3 4 1808 1808-04-01 12:00:00 blood 712 #> 1424 12.3 4 1808 1808-04-01 12:00:00 bone 712 #> 1425 13.5 5 1808 1808-05-02 00:00:00 blood 713 #> 1426 13.5 5 1808 1808-05-02 00:00:00 bone 713 #> 1427 13.5 6 1808 1808-06-01 12:00:01 blood 714 #> 1428 13.5 6 1808 1808-06-01 12:00:01 bone 714 #> 1429 6.7 7 1808 1808-07-02 00:00:00 blood 715 #> 1430 6.7 7 1808 1808-07-02 00:00:00 bone 715 #> 1431 8.0 8 1808 1808-08-01 12:00:00 blood 716 #> 1432 8.0 8 1808 1808-08-01 12:00:00 bone 716 #> 1433 11.7 9 1808 1808-09-01 00:00:01 blood 717 #> 1434 11.7 9 1808 1808-09-01 00:00:01 bone 717 #> 1435 4.7 10 1808 1808-10-01 12:00:00 blood 718 #> 1436 4.7 10 1808 1808-10-01 12:00:00 bone 718 #> 1437 10.5 11 1808 1808-11-01 00:00:00 blood 719 #> 1438 10.5 11 1808 1808-11-01 00:00:00 bone 719 #> 1439 12.3 12 1808 1808-12-01 12:00:01 blood 720 #> 1440 12.3 12 1808 1808-12-01 12:00:01 bone 720 #> 1441 7.2 1 1809 1809-01-01 00:00:00 blood 721 #> 1442 7.2 1 1809 1809-01-01 00:00:00 bone 721 #> 1443 9.2 2 1809 1809-01-31 10:00:00 blood 722 #> 1444 9.2 2 1809 1809-01-31 10:00:00 bone 722 #> 1445 0.9 3 1809 1809-03-02 20:00:01 blood 723 #> 1446 0.9 3 1809 1809-03-02 20:00:01 bone 723 #> 1447 2.5 4 1809 1809-04-02 06:00:00 blood 724 #> 1448 2.5 4 1809 1809-04-02 06:00:00 bone 724 #> 1449 2.0 5 1809 1809-05-02 16:00:00 blood 725 #> 1450 2.0 5 1809 1809-05-02 16:00:00 bone 725 #> 1451 7.7 6 1809 1809-06-02 02:00:01 blood 726 #> 1452 7.7 6 1809 1809-06-02 02:00:01 bone 726 #> 1453 0.3 7 1809 1809-07-02 12:00:00 blood 727 #> 1454 0.3 7 1809 1809-07-02 12:00:00 bone 727 #> 1455 0.2 8 1809 1809-08-01 22:00:00 blood 728 #> 1456 0.2 8 1809 1809-08-01 22:00:00 bone 728 #> 1457 0.4 9 1809 1809-09-01 08:00:01 blood 729 #> 1458 0.4 9 1809 1809-09-01 08:00:01 bone 729 #> 1459 0.0 10 1809 1809-10-01 18:00:00 blood 730 #> 1460 0.0 10 1809 1809-10-01 18:00:00 bone 730 #> 1461 0.0 11 1809 1809-11-01 04:00:00 blood 731 #> 1462 0.0 11 1809 1809-11-01 04:00:00 bone 731 #> 1463 0.0 12 1809 1809-12-01 14:00:01 blood 732 #> 1464 0.0 12 1809 1809-12-01 14:00:01 bone 732 #> 1465 0.0 1 1810 1810-01-01 00:00:00 blood 733 #> 1466 0.0 1 1810 1810-01-01 00:00:00 bone 733 #> 1467 0.0 2 1810 1810-01-31 10:00:00 blood 734 #> 1468 0.0 2 1810 1810-01-31 10:00:00 bone 734 #> 1469 0.0 3 1810 1810-03-02 20:00:01 blood 735 #> 1470 0.0 3 1810 1810-03-02 20:00:01 bone 735 #> 1471 0.0 4 1810 1810-04-02 06:00:00 blood 736 #> 1472 0.0 4 1810 1810-04-02 06:00:00 bone 736 #> 1473 0.0 5 1810 1810-05-02 16:00:00 blood 737 #> 1474 0.0 5 1810 1810-05-02 16:00:00 bone 737 #> 1475 0.0 6 1810 1810-06-02 02:00:01 blood 738 #> 1476 0.0 6 1810 1810-06-02 02:00:01 bone 738 #> 1477 0.0 7 1810 1810-07-02 12:00:00 blood 739 #> 1478 0.0 7 1810 1810-07-02 12:00:00 bone 739 #> 1479 0.0 8 1810 1810-08-01 22:00:00 blood 740 #> 1480 0.0 8 1810 1810-08-01 22:00:00 bone 740 #> 1481 0.0 9 1810 1810-09-01 08:00:01 blood 741 #> 1482 0.0 9 1810 1810-09-01 08:00:01 bone 741 #> 1483 0.0 10 1810 1810-10-01 18:00:00 blood 742 #> 1484 0.0 10 1810 1810-10-01 18:00:00 bone 742 #> 1485 0.0 11 1810 1810-11-01 04:00:00 blood 743 #> 1486 0.0 11 1810 1810-11-01 04:00:00 bone 743 #> 1487 0.0 12 1810 1810-12-01 14:00:01 blood 744 #> 1488 0.0 12 1810 1810-12-01 14:00:01 bone 744 #> 1489 0.0 1 1811 1811-01-01 00:00:00 blood 745 #> 1490 0.0 1 1811 1811-01-01 00:00:00 bone 745 #> 1491 0.0 2 1811 1811-01-31 10:00:00 blood 746 #> 1492 0.0 2 1811 1811-01-31 10:00:00 bone 746 #> 1493 0.0 3 1811 1811-03-02 20:00:01 blood 747 #> 1494 0.0 3 1811 1811-03-02 20:00:01 bone 747 #> 1495 0.0 4 1811 1811-04-02 06:00:00 blood 748 #> 1496 0.0 4 1811 1811-04-02 06:00:00 bone 748 #> 1497 0.0 5 1811 1811-05-02 16:00:00 blood 749 #> 1498 0.0 5 1811 1811-05-02 16:00:00 bone 749 #> 1499 0.0 6 1811 1811-06-02 02:00:01 blood 750 #> 1500 0.0 6 1811 1811-06-02 02:00:01 bone 750 #> 1501 6.6 7 1811 1811-07-02 12:00:00 blood 751 #> 1502 6.6 7 1811 1811-07-02 12:00:00 bone 751 #> 1503 0.0 8 1811 1811-08-01 22:00:00 blood 752 #> 1504 0.0 8 1811 1811-08-01 22:00:00 bone 752 #> 1505 2.4 9 1811 1811-09-01 08:00:01 blood 753 #> 1506 2.4 9 1811 1811-09-01 08:00:01 bone 753 #> 1507 6.1 10 1811 1811-10-01 18:00:00 blood 754 #> 1508 6.1 10 1811 1811-10-01 18:00:00 bone 754 #> 1509 0.8 11 1811 1811-11-01 04:00:00 blood 755 #> 1510 0.8 11 1811 1811-11-01 04:00:00 bone 755 #> 1511 1.1 12 1811 1811-12-01 14:00:01 blood 756 #> 1512 1.1 12 1811 1811-12-01 14:00:01 bone 756 #> 1513 11.3 1 1812 1812-01-01 00:00:00 blood 757 #> 1514 11.3 1 1812 1812-01-01 00:00:00 bone 757 #> 1515 1.9 2 1812 1812-01-31 12:00:00 blood 758 #> 1516 1.9 2 1812 1812-01-31 12:00:00 bone 758 #> 1517 0.7 3 1812 1812-03-02 00:00:01 blood 759 #> 1518 0.7 3 1812 1812-03-02 00:00:01 bone 759 #> 1519 0.0 4 1812 1812-04-01 12:00:00 blood 760 #> 1520 0.0 4 1812 1812-04-01 12:00:00 bone 760 #> 1521 1.0 5 1812 1812-05-02 00:00:00 blood 761 #> 1522 1.0 5 1812 1812-05-02 00:00:00 bone 761 #> 1523 1.3 6 1812 1812-06-01 12:00:01 blood 762 #> 1524 1.3 6 1812 1812-06-01 12:00:01 bone 762 #> 1525 0.5 7 1812 1812-07-02 00:00:00 blood 763 #> 1526 0.5 7 1812 1812-07-02 00:00:00 bone 763 #> 1527 15.6 8 1812 1812-08-01 12:00:00 blood 764 #> 1528 15.6 8 1812 1812-08-01 12:00:00 bone 764 #> 1529 5.2 9 1812 1812-09-01 00:00:01 blood 765 #> 1530 5.2 9 1812 1812-09-01 00:00:01 bone 765 #> 1531 3.9 10 1812 1812-10-01 12:00:00 blood 766 #> 1532 3.9 10 1812 1812-10-01 12:00:00 bone 766 #> 1533 7.9 11 1812 1812-11-01 00:00:00 blood 767 #> 1534 7.9 11 1812 1812-11-01 00:00:00 bone 767 #> 1535 10.1 12 1812 1812-12-01 12:00:01 blood 768 #> 1536 10.1 12 1812 1812-12-01 12:00:01 bone 768 #> 1537 0.0 1 1813 1813-01-01 00:00:00 blood 769 #> 1538 0.0 1 1813 1813-01-01 00:00:00 bone 769 #> 1539 10.3 2 1813 1813-01-31 10:00:00 blood 770 #> 1540 10.3 2 1813 1813-01-31 10:00:00 bone 770 #> 1541 1.9 3 1813 1813-03-02 20:00:01 blood 771 #> 1542 1.9 3 1813 1813-03-02 20:00:01 bone 771 #> 1543 16.6 4 1813 1813-04-02 06:00:00 blood 772 #> 1544 16.6 4 1813 1813-04-02 06:00:00 bone 772 #> 1545 5.5 5 1813 1813-05-02 16:00:00 blood 773 #> 1546 5.5 5 1813 1813-05-02 16:00:00 bone 773 #> 1547 11.2 6 1813 1813-06-02 02:00:01 blood 774 #> 1548 11.2 6 1813 1813-06-02 02:00:01 bone 774 #> 1549 18.3 7 1813 1813-07-02 12:00:00 blood 775 #> 1550 18.3 7 1813 1813-07-02 12:00:00 bone 775 #> 1551 8.4 8 1813 1813-08-01 22:00:00 blood 776 #> 1552 8.4 8 1813 1813-08-01 22:00:00 bone 776 #> 1553 15.3 9 1813 1813-09-01 08:00:01 blood 777 #> 1554 15.3 9 1813 1813-09-01 08:00:01 bone 777 #> 1555 27.8 10 1813 1813-10-01 18:00:00 blood 778 #> 1556 27.8 10 1813 1813-10-01 18:00:00 bone 778 #> 1557 16.7 11 1813 1813-11-01 04:00:00 blood 779 #> 1558 16.7 11 1813 1813-11-01 04:00:00 bone 779 #> 1559 14.3 12 1813 1813-12-01 14:00:01 blood 780 #> 1560 14.3 12 1813 1813-12-01 14:00:01 bone 780 #> 1561 22.2 1 1814 1814-01-01 00:00:00 blood 781 #> 1562 22.2 1 1814 1814-01-01 00:00:00 bone 781 #> 1563 12.0 2 1814 1814-01-31 10:00:00 blood 782 #> 1564 12.0 2 1814 1814-01-31 10:00:00 bone 782 #> 1565 5.7 3 1814 1814-03-02 20:00:01 blood 783 #> 1566 5.7 3 1814 1814-03-02 20:00:01 bone 783 #> 1567 23.8 4 1814 1814-04-02 06:00:00 blood 784 #> 1568 23.8 4 1814 1814-04-02 06:00:00 bone 784 #> 1569 5.8 5 1814 1814-05-02 16:00:00 blood 785 #> 1570 5.8 5 1814 1814-05-02 16:00:00 bone 785 #> 1571 14.9 6 1814 1814-06-02 02:00:01 blood 786 #> 1572 14.9 6 1814 1814-06-02 02:00:01 bone 786 #> 1573 18.5 7 1814 1814-07-02 12:00:00 blood 787 #> 1574 18.5 7 1814 1814-07-02 12:00:00 bone 787 #> 1575 2.3 8 1814 1814-08-01 22:00:00 blood 788 #> 1576 2.3 8 1814 1814-08-01 22:00:00 bone 788 #> 1577 8.1 9 1814 1814-09-01 08:00:01 blood 789 #> 1578 8.1 9 1814 1814-09-01 08:00:01 bone 789 #> 1579 19.3 10 1814 1814-10-01 18:00:00 blood 790 #> 1580 19.3 10 1814 1814-10-01 18:00:00 bone 790 #> 1581 14.5 11 1814 1814-11-01 04:00:00 blood 791 #> 1582 14.5 11 1814 1814-11-01 04:00:00 bone 791 #> 1583 20.1 12 1814 1814-12-01 14:00:01 blood 792 #> 1584 20.1 12 1814 1814-12-01 14:00:01 bone 792 #> 1585 19.2 1 1815 1815-01-01 00:00:00 blood 793 #> 1586 19.2 1 1815 1815-01-01 00:00:00 bone 793 #> 1587 32.2 2 1815 1815-01-31 10:00:00 blood 794 #> 1588 32.2 2 1815 1815-01-31 10:00:00 bone 794 #> 1589 26.2 3 1815 1815-03-02 20:00:01 blood 795 #> 1590 26.2 3 1815 1815-03-02 20:00:01 bone 795 #> 1591 31.6 4 1815 1815-04-02 06:00:00 blood 796 #> 1592 31.6 4 1815 1815-04-02 06:00:00 bone 796 #> 1593 9.8 5 1815 1815-05-02 16:00:00 blood 797 #> 1594 9.8 5 1815 1815-05-02 16:00:00 bone 797 #> 1595 55.9 6 1815 1815-06-02 02:00:01 blood 798 #> 1596 55.9 6 1815 1815-06-02 02:00:01 bone 798 #> 1597 35.5 7 1815 1815-07-02 12:00:00 blood 799 #> 1598 35.5 7 1815 1815-07-02 12:00:00 bone 799 #> 1599 47.2 8 1815 1815-08-01 22:00:00 blood 800 #> 1600 47.2 8 1815 1815-08-01 22:00:00 bone 800 #> 1601 31.5 9 1815 1815-09-01 08:00:01 blood 801 #> 1602 31.5 9 1815 1815-09-01 08:00:01 bone 801 #> 1603 33.5 10 1815 1815-10-01 18:00:00 blood 802 #> 1604 33.5 10 1815 1815-10-01 18:00:00 bone 802 #> 1605 37.2 11 1815 1815-11-01 04:00:00 blood 803 #> 1606 37.2 11 1815 1815-11-01 04:00:00 bone 803 #> 1607 65.0 12 1815 1815-12-01 14:00:01 blood 804 #> 1608 65.0 12 1815 1815-12-01 14:00:01 bone 804 #> 1609 26.3 1 1816 1816-01-01 00:00:00 blood 805 #> 1610 26.3 1 1816 1816-01-01 00:00:00 bone 805 #> 1611 68.8 2 1816 1816-01-31 12:00:00 blood 806 #> 1612 68.8 2 1816 1816-01-31 12:00:00 bone 806 #> 1613 73.7 3 1816 1816-03-02 00:00:01 blood 807 #> 1614 73.7 3 1816 1816-03-02 00:00:01 bone 807 #> 1615 58.8 4 1816 1816-04-01 12:00:00 blood 808 #> 1616 58.8 4 1816 1816-04-01 12:00:00 bone 808 #> 1617 44.3 5 1816 1816-05-02 00:00:00 blood 809 #> 1618 44.3 5 1816 1816-05-02 00:00:00 bone 809 #> 1619 43.6 6 1816 1816-06-01 12:00:01 blood 810 #> 1620 43.6 6 1816 1816-06-01 12:00:01 bone 810 #> 1621 38.8 7 1816 1816-07-02 00:00:00 blood 811 #> 1622 38.8 7 1816 1816-07-02 00:00:00 bone 811 #> 1623 23.2 8 1816 1816-08-01 12:00:00 blood 812 #> 1624 23.2 8 1816 1816-08-01 12:00:00 bone 812 #> 1625 47.8 9 1816 1816-09-01 00:00:01 blood 813 #> 1626 47.8 9 1816 1816-09-01 00:00:01 bone 813 #> 1627 56.4 10 1816 1816-10-01 12:00:00 blood 814 #> 1628 56.4 10 1816 1816-10-01 12:00:00 bone 814 #> 1629 38.1 11 1816 1816-11-01 00:00:00 blood 815 #> 1630 38.1 11 1816 1816-11-01 00:00:00 bone 815 #> 1631 29.9 12 1816 1816-12-01 12:00:01 blood 816 #> 1632 29.9 12 1816 1816-12-01 12:00:01 bone 816 #> 1633 36.4 1 1817 1817-01-01 00:00:00 blood 817 #> 1634 36.4 1 1817 1817-01-01 00:00:00 bone 817 #> 1635 57.9 2 1817 1817-01-31 10:00:00 blood 818 #> 1636 57.9 2 1817 1817-01-31 10:00:00 bone 818 #> 1637 96.2 3 1817 1817-03-02 20:00:01 blood 819 #> 1638 96.2 3 1817 1817-03-02 20:00:01 bone 819 #> 1639 26.4 4 1817 1817-04-02 06:00:00 blood 820 #> 1640 26.4 4 1817 1817-04-02 06:00:00 bone 820 #> 1641 21.2 5 1817 1817-05-02 16:00:00 blood 821 #> 1642 21.2 5 1817 1817-05-02 16:00:00 bone 821 #> 1643 40.0 6 1817 1817-06-02 02:00:01 blood 822 #> 1644 40.0 6 1817 1817-06-02 02:00:01 bone 822 #> 1645 50.0 7 1817 1817-07-02 12:00:00 blood 823 #> 1646 50.0 7 1817 1817-07-02 12:00:00 bone 823 #> 1647 45.0 8 1817 1817-08-01 22:00:00 blood 824 #> 1648 45.0 8 1817 1817-08-01 22:00:00 bone 824 #> 1649 36.7 9 1817 1817-09-01 08:00:01 blood 825 #> 1650 36.7 9 1817 1817-09-01 08:00:01 bone 825 #> 1651 25.6 10 1817 1817-10-01 18:00:00 blood 826 #> 1652 25.6 10 1817 1817-10-01 18:00:00 bone 826 #> 1653 28.9 11 1817 1817-11-01 04:00:00 blood 827 #> 1654 28.9 11 1817 1817-11-01 04:00:00 bone 827 #> 1655 28.4 12 1817 1817-12-01 14:00:01 blood 828 #> 1656 28.4 12 1817 1817-12-01 14:00:01 bone 828 #> 1657 34.9 1 1818 1818-01-01 00:00:00 blood 829 #> 1658 34.9 1 1818 1818-01-01 00:00:00 bone 829 #> 1659 22.4 2 1818 1818-01-31 10:00:00 blood 830 #> 1660 22.4 2 1818 1818-01-31 10:00:00 bone 830 #> 1661 25.4 3 1818 1818-03-02 20:00:01 blood 831 #> 1662 25.4 3 1818 1818-03-02 20:00:01 bone 831 #> 1663 34.5 4 1818 1818-04-02 06:00:00 blood 832 #> 1664 34.5 4 1818 1818-04-02 06:00:00 bone 832 #> 1665 53.1 5 1818 1818-05-02 16:00:00 blood 833 #> 1666 53.1 5 1818 1818-05-02 16:00:00 bone 833 #> 1667 36.4 6 1818 1818-06-02 02:00:01 blood 834 #> 1668 36.4 6 1818 1818-06-02 02:00:01 bone 834 #> 1669 28.0 7 1818 1818-07-02 12:00:00 blood 835 #> 1670 28.0 7 1818 1818-07-02 12:00:00 bone 835 #> 1671 31.5 8 1818 1818-08-01 22:00:00 blood 836 #> 1672 31.5 8 1818 1818-08-01 22:00:00 bone 836 #> 1673 26.1 9 1818 1818-09-01 08:00:01 blood 837 #> 1674 26.1 9 1818 1818-09-01 08:00:01 bone 837 #> 1675 31.7 10 1818 1818-10-01 18:00:00 blood 838 #> 1676 31.7 10 1818 1818-10-01 18:00:00 bone 838 #> 1677 10.9 11 1818 1818-11-01 04:00:00 blood 839 #> 1678 10.9 11 1818 1818-11-01 04:00:00 bone 839 #> 1679 25.8 12 1818 1818-12-01 14:00:01 blood 840 #> 1680 25.8 12 1818 1818-12-01 14:00:01 bone 840 #> 1681 32.5 1 1819 1819-01-01 00:00:00 blood 841 #> 1682 32.5 1 1819 1819-01-01 00:00:00 bone 841 #> 1683 20.7 2 1819 1819-01-31 10:00:00 blood 842 #> 1684 20.7 2 1819 1819-01-31 10:00:00 bone 842 #> 1685 3.7 3 1819 1819-03-02 20:00:01 blood 843 #> 1686 3.7 3 1819 1819-03-02 20:00:01 bone 843 #> 1687 20.2 4 1819 1819-04-02 06:00:00 blood 844 #> 1688 20.2 4 1819 1819-04-02 06:00:00 bone 844 #> 1689 19.6 5 1819 1819-05-02 16:00:00 blood 845 #> 1690 19.6 5 1819 1819-05-02 16:00:00 bone 845 #> 1691 35.0 6 1819 1819-06-02 02:00:01 blood 846 #> 1692 35.0 6 1819 1819-06-02 02:00:01 bone 846 #> 1693 31.4 7 1819 1819-07-02 12:00:00 blood 847 #> 1694 31.4 7 1819 1819-07-02 12:00:00 bone 847 #> 1695 26.1 8 1819 1819-08-01 22:00:00 blood 848 #> 1696 26.1 8 1819 1819-08-01 22:00:00 bone 848 #> 1697 14.9 9 1819 1819-09-01 08:00:01 blood 849 #> 1698 14.9 9 1819 1819-09-01 08:00:01 bone 849 #> 1699 27.5 10 1819 1819-10-01 18:00:00 blood 850 #> 1700 27.5 10 1819 1819-10-01 18:00:00 bone 850 #> 1701 25.1 11 1819 1819-11-01 04:00:00 blood 851 #> 1702 25.1 11 1819 1819-11-01 04:00:00 bone 851 #> 1703 30.6 12 1819 1819-12-01 14:00:01 blood 852 #> 1704 30.6 12 1819 1819-12-01 14:00:01 bone 852 #> 1705 19.2 1 1820 1820-01-01 00:00:00 blood 853 #> 1706 19.2 1 1820 1820-01-01 00:00:00 bone 853 #> 1707 26.6 2 1820 1820-01-31 12:00:00 blood 854 #> 1708 26.6 2 1820 1820-01-31 12:00:00 bone 854 #> 1709 4.5 3 1820 1820-03-02 00:00:01 blood 855 #> 1710 4.5 3 1820 1820-03-02 00:00:01 bone 855 #> 1711 19.4 4 1820 1820-04-01 12:00:00 blood 856 #> 1712 19.4 4 1820 1820-04-01 12:00:00 bone 856 #> 1713 29.3 5 1820 1820-05-02 00:00:00 blood 857 #> 1714 29.3 5 1820 1820-05-02 00:00:00 bone 857 #> 1715 10.8 6 1820 1820-06-01 12:00:01 blood 858 #> 1716 10.8 6 1820 1820-06-01 12:00:01 bone 858 #> 1717 20.6 7 1820 1820-07-02 00:00:00 blood 859 #> 1718 20.6 7 1820 1820-07-02 00:00:00 bone 859 #> 1719 25.9 8 1820 1820-08-01 12:00:00 blood 860 #> 1720 25.9 8 1820 1820-08-01 12:00:00 bone 860 #> 1721 5.2 9 1820 1820-09-01 00:00:01 blood 861 #> 1722 5.2 9 1820 1820-09-01 00:00:01 bone 861 #> 1723 9.0 10 1820 1820-10-01 12:00:00 blood 862 #> 1724 9.0 10 1820 1820-10-01 12:00:00 bone 862 #> 1725 7.9 11 1820 1820-11-01 00:00:00 blood 863 #> 1726 7.9 11 1820 1820-11-01 00:00:00 bone 863 #> 1727 9.7 12 1820 1820-12-01 12:00:01 blood 864 #> 1728 9.7 12 1820 1820-12-01 12:00:01 bone 864 #> 1729 21.5 1 1821 1821-01-01 00:00:00 blood 865 #> 1730 21.5 1 1821 1821-01-01 00:00:00 bone 865 #> 1731 4.3 2 1821 1821-01-31 10:00:00 blood 866 #> 1732 4.3 2 1821 1821-01-31 10:00:00 bone 866 #> 1733 5.7 3 1821 1821-03-02 20:00:01 blood 867 #> 1734 5.7 3 1821 1821-03-02 20:00:01 bone 867 #> 1735 9.2 4 1821 1821-04-02 06:00:00 blood 868 #> 1736 9.2 4 1821 1821-04-02 06:00:00 bone 868 #> 1737 1.7 5 1821 1821-05-02 16:00:00 blood 869 #> 1738 1.7 5 1821 1821-05-02 16:00:00 bone 869 #> 1739 1.8 6 1821 1821-06-02 02:00:01 blood 870 #> 1740 1.8 6 1821 1821-06-02 02:00:01 bone 870 #> 1741 2.5 7 1821 1821-07-02 12:00:00 blood 871 #> 1742 2.5 7 1821 1821-07-02 12:00:00 bone 871 #> 1743 4.8 8 1821 1821-08-01 22:00:00 blood 872 #> 1744 4.8 8 1821 1821-08-01 22:00:00 bone 872 #> 1745 4.4 9 1821 1821-09-01 08:00:01 blood 873 #> 1746 4.4 9 1821 1821-09-01 08:00:01 bone 873 #> 1747 18.8 10 1821 1821-10-01 18:00:00 blood 874 #> 1748 18.8 10 1821 1821-10-01 18:00:00 bone 874 #> 1749 4.4 11 1821 1821-11-01 04:00:00 blood 875 #> 1750 4.4 11 1821 1821-11-01 04:00:00 bone 875 #> 1751 0.0 12 1821 1821-12-01 14:00:01 blood 876 #> 1752 0.0 12 1821 1821-12-01 14:00:01 bone 876 #> 1753 0.0 1 1822 1822-01-01 00:00:00 blood 877 #> 1754 0.0 1 1822 1822-01-01 00:00:00 bone 877 #> 1755 0.9 2 1822 1822-01-31 10:00:00 blood 878 #> 1756 0.9 2 1822 1822-01-31 10:00:00 bone 878 #> 1757 16.1 3 1822 1822-03-02 20:00:01 blood 879 #> 1758 16.1 3 1822 1822-03-02 20:00:01 bone 879 #> 1759 13.5 4 1822 1822-04-02 06:00:00 blood 880 #> 1760 13.5 4 1822 1822-04-02 06:00:00 bone 880 #> 1761 1.5 5 1822 1822-05-02 16:00:00 blood 881 #> 1762 1.5 5 1822 1822-05-02 16:00:00 bone 881 #> 1763 5.6 6 1822 1822-06-02 02:00:01 blood 882 #> 1764 5.6 6 1822 1822-06-02 02:00:01 bone 882 #> 1765 7.9 7 1822 1822-07-02 12:00:00 blood 883 #> 1766 7.9 7 1822 1822-07-02 12:00:00 bone 883 #> 1767 2.1 8 1822 1822-08-01 22:00:00 blood 884 #> 1768 2.1 8 1822 1822-08-01 22:00:00 bone 884 #> 1769 0.0 9 1822 1822-09-01 08:00:01 blood 885 #> 1770 0.0 9 1822 1822-09-01 08:00:01 bone 885 #> 1771 0.4 10 1822 1822-10-01 18:00:00 blood 886 #> 1772 0.4 10 1822 1822-10-01 18:00:00 bone 886 #> 1773 0.0 11 1822 1822-11-01 04:00:00 blood 887 #> 1774 0.0 11 1822 1822-11-01 04:00:00 bone 887 #> 1775 0.0 12 1822 1822-12-01 14:00:01 blood 888 #> 1776 0.0 12 1822 1822-12-01 14:00:01 bone 888 #> 1777 0.0 1 1823 1823-01-01 00:00:00 blood 889 #> 1778 0.0 1 1823 1823-01-01 00:00:00 bone 889 #> 1779 0.0 2 1823 1823-01-31 10:00:00 blood 890 #> 1780 0.0 2 1823 1823-01-31 10:00:00 bone 890 #> 1781 0.6 3 1823 1823-03-02 20:00:01 blood 891 #> 1782 0.6 3 1823 1823-03-02 20:00:01 bone 891 #> 1783 0.0 4 1823 1823-04-02 06:00:00 blood 892 #> 1784 0.0 4 1823 1823-04-02 06:00:00 bone 892 #> 1785 0.0 5 1823 1823-05-02 16:00:00 blood 893 #> 1786 0.0 5 1823 1823-05-02 16:00:00 bone 893 #> 1787 0.0 6 1823 1823-06-02 02:00:01 blood 894 #> 1788 0.0 6 1823 1823-06-02 02:00:01 bone 894 #> 1789 0.5 7 1823 1823-07-02 12:00:00 blood 895 #> 1790 0.5 7 1823 1823-07-02 12:00:00 bone 895 #> 1791 0.0 8 1823 1823-08-01 22:00:00 blood 896 #> 1792 0.0 8 1823 1823-08-01 22:00:00 bone 896 #> 1793 0.0 9 1823 1823-09-01 08:00:01 blood 897 #> 1794 0.0 9 1823 1823-09-01 08:00:01 bone 897 #> 1795 0.0 10 1823 1823-10-01 18:00:00 blood 898 #> 1796 0.0 10 1823 1823-10-01 18:00:00 bone 898 #> 1797 0.0 11 1823 1823-11-01 04:00:00 blood 899 #> 1798 0.0 11 1823 1823-11-01 04:00:00 bone 899 #> 1799 20.4 12 1823 1823-12-01 14:00:01 blood 900 #> 1800 20.4 12 1823 1823-12-01 14:00:01 bone 900 #> 1801 21.6 1 1824 1824-01-01 00:00:00 blood 901 #> 1802 21.6 1 1824 1824-01-01 00:00:00 bone 901 #> 1803 10.8 2 1824 1824-01-31 12:00:00 blood 902 #> 1804 10.8 2 1824 1824-01-31 12:00:00 bone 902 #> 1805 0.0 3 1824 1824-03-02 00:00:01 blood 903 #> 1806 0.0 3 1824 1824-03-02 00:00:01 bone 903 #> 1807 19.4 4 1824 1824-04-01 12:00:00 blood 904 #> 1808 19.4 4 1824 1824-04-01 12:00:00 bone 904 #> 1809 2.8 5 1824 1824-05-02 00:00:00 blood 905 #> 1810 2.8 5 1824 1824-05-02 00:00:00 bone 905 #> 1811 0.0 6 1824 1824-06-01 12:00:01 blood 906 #> 1812 0.0 6 1824 1824-06-01 12:00:01 bone 906 #> 1813 0.0 7 1824 1824-07-02 00:00:00 blood 907 #> 1814 0.0 7 1824 1824-07-02 00:00:00 bone 907 #> 1815 1.4 8 1824 1824-08-01 12:00:00 blood 908 #> 1816 1.4 8 1824 1824-08-01 12:00:00 bone 908 #> 1817 20.5 9 1824 1824-09-01 00:00:01 blood 909 #> 1818 20.5 9 1824 1824-09-01 00:00:01 bone 909 #> 1819 25.2 10 1824 1824-10-01 12:00:00 blood 910 #> 1820 25.2 10 1824 1824-10-01 12:00:00 bone 910 #> 1821 0.0 11 1824 1824-11-01 00:00:00 blood 911 #> 1822 0.0 11 1824 1824-11-01 00:00:00 bone 911 #> 1823 0.8 12 1824 1824-12-01 12:00:01 blood 912 #> 1824 0.8 12 1824 1824-12-01 12:00:01 bone 912 #> 1825 5.0 1 1825 1825-01-01 00:00:00 blood 913 #> 1826 5.0 1 1825 1825-01-01 00:00:00 bone 913 #> 1827 15.5 2 1825 1825-01-31 10:00:00 blood 914 #> 1828 15.5 2 1825 1825-01-31 10:00:00 bone 914 #> 1829 22.4 3 1825 1825-03-02 20:00:01 blood 915 #> 1830 22.4 3 1825 1825-03-02 20:00:01 bone 915 #> 1831 3.8 4 1825 1825-04-02 06:00:00 blood 916 #> 1832 3.8 4 1825 1825-04-02 06:00:00 bone 916 #> 1833 15.4 5 1825 1825-05-02 16:00:00 blood 917 #> 1834 15.4 5 1825 1825-05-02 16:00:00 bone 917 #> 1835 15.4 6 1825 1825-06-02 02:00:01 blood 918 #> 1836 15.4 6 1825 1825-06-02 02:00:01 bone 918 #> 1837 30.9 7 1825 1825-07-02 12:00:00 blood 919 #> 1838 30.9 7 1825 1825-07-02 12:00:00 bone 919 #> 1839 25.4 8 1825 1825-08-01 22:00:00 blood 920 #> 1840 25.4 8 1825 1825-08-01 22:00:00 bone 920 #> 1841 15.7 9 1825 1825-09-01 08:00:01 blood 921 #> 1842 15.7 9 1825 1825-09-01 08:00:01 bone 921 #> 1843 15.6 10 1825 1825-10-01 18:00:00 blood 922 #> 1844 15.6 10 1825 1825-10-01 18:00:00 bone 922 #> 1845 11.7 11 1825 1825-11-01 04:00:00 blood 923 #> 1846 11.7 11 1825 1825-11-01 04:00:00 bone 923 #> 1847 22.0 12 1825 1825-12-01 14:00:01 blood 924 #> 1848 22.0 12 1825 1825-12-01 14:00:01 bone 924 #> 1849 17.7 1 1826 1826-01-01 00:00:00 blood 925 #> 1850 17.7 1 1826 1826-01-01 00:00:00 bone 925 #> 1851 18.2 2 1826 1826-01-31 10:00:00 blood 926 #> 1852 18.2 2 1826 1826-01-31 10:00:00 bone 926 #> 1853 36.7 3 1826 1826-03-02 20:00:01 blood 927 #> 1854 36.7 3 1826 1826-03-02 20:00:01 bone 927 #> 1855 24.0 4 1826 1826-04-02 06:00:00 blood 928 #> 1856 24.0 4 1826 1826-04-02 06:00:00 bone 928 #> 1857 32.4 5 1826 1826-05-02 16:00:00 blood 929 #> 1858 32.4 5 1826 1826-05-02 16:00:00 bone 929 #> 1859 37.1 6 1826 1826-06-02 02:00:01 blood 930 #> 1860 37.1 6 1826 1826-06-02 02:00:01 bone 930 #> 1861 52.5 7 1826 1826-07-02 12:00:00 blood 931 #> 1862 52.5 7 1826 1826-07-02 12:00:00 bone 931 #> 1863 39.6 8 1826 1826-08-01 22:00:00 blood 932 #> 1864 39.6 8 1826 1826-08-01 22:00:00 bone 932 #> 1865 18.9 9 1826 1826-09-01 08:00:01 blood 933 #> 1866 18.9 9 1826 1826-09-01 08:00:01 bone 933 #> 1867 50.6 10 1826 1826-10-01 18:00:00 blood 934 #> 1868 50.6 10 1826 1826-10-01 18:00:00 bone 934 #> 1869 39.5 11 1826 1826-11-01 04:00:00 blood 935 #> 1870 39.5 11 1826 1826-11-01 04:00:00 bone 935 #> 1871 68.1 12 1826 1826-12-01 14:00:01 blood 936 #> 1872 68.1 12 1826 1826-12-01 14:00:01 bone 936 #> 1873 34.6 1 1827 1827-01-01 00:00:00 blood 937 #> 1874 34.6 1 1827 1827-01-01 00:00:00 bone 937 #> 1875 47.4 2 1827 1827-01-31 10:00:00 blood 938 #> 1876 47.4 2 1827 1827-01-31 10:00:00 bone 938 #> 1877 57.8 3 1827 1827-03-02 20:00:01 blood 939 #> 1878 57.8 3 1827 1827-03-02 20:00:01 bone 939 #> 1879 46.0 4 1827 1827-04-02 06:00:00 blood 940 #> 1880 46.0 4 1827 1827-04-02 06:00:00 bone 940 #> 1881 56.3 5 1827 1827-05-02 16:00:00 blood 941 #> 1882 56.3 5 1827 1827-05-02 16:00:00 bone 941 #> 1883 56.7 6 1827 1827-06-02 02:00:01 blood 942 #> 1884 56.7 6 1827 1827-06-02 02:00:01 bone 942 #> 1885 42.9 7 1827 1827-07-02 12:00:00 blood 943 #> 1886 42.9 7 1827 1827-07-02 12:00:00 bone 943 #> 1887 53.7 8 1827 1827-08-01 22:00:00 blood 944 #> 1888 53.7 8 1827 1827-08-01 22:00:00 bone 944 #> 1889 49.6 9 1827 1827-09-01 08:00:01 blood 945 #> 1890 49.6 9 1827 1827-09-01 08:00:01 bone 945 #> 1891 57.2 10 1827 1827-10-01 18:00:00 blood 946 #> 1892 57.2 10 1827 1827-10-01 18:00:00 bone 946 #> 1893 48.2 11 1827 1827-11-01 04:00:00 blood 947 #> 1894 48.2 11 1827 1827-11-01 04:00:00 bone 947 #> 1895 46.1 12 1827 1827-12-01 14:00:01 blood 948 #> 1896 46.1 12 1827 1827-12-01 14:00:01 bone 948 #> 1897 52.8 1 1828 1828-01-01 00:00:00 blood 949 #> 1898 52.8 1 1828 1828-01-01 00:00:00 bone 949 #> 1899 64.4 2 1828 1828-01-31 12:00:00 blood 950 #> 1900 64.4 2 1828 1828-01-31 12:00:00 bone 950 #> 1901 65.0 3 1828 1828-03-02 00:00:01 blood 951 #> 1902 65.0 3 1828 1828-03-02 00:00:01 bone 951 #> 1903 61.1 4 1828 1828-04-01 12:00:00 blood 952 #> 1904 61.1 4 1828 1828-04-01 12:00:00 bone 952 #> 1905 89.1 5 1828 1828-05-02 00:00:00 blood 953 #> 1906 89.1 5 1828 1828-05-02 00:00:00 bone 953 #> 1907 98.0 6 1828 1828-06-01 12:00:01 blood 954 #> 1908 98.0 6 1828 1828-06-01 12:00:01 bone 954 #> 1909 54.3 7 1828 1828-07-02 00:00:00 blood 955 #> 1910 54.3 7 1828 1828-07-02 00:00:00 bone 955 #> 1911 76.4 8 1828 1828-08-01 12:00:00 blood 956 #> 1912 76.4 8 1828 1828-08-01 12:00:00 bone 956 #> 1913 50.4 9 1828 1828-09-01 00:00:01 blood 957 #> 1914 50.4 9 1828 1828-09-01 00:00:01 bone 957 #> 1915 54.7 10 1828 1828-10-01 12:00:00 blood 958 #> 1916 54.7 10 1828 1828-10-01 12:00:00 bone 958 #> 1917 57.0 11 1828 1828-11-01 00:00:00 blood 959 #> 1918 57.0 11 1828 1828-11-01 00:00:00 bone 959 #> 1919 46.6 12 1828 1828-12-01 12:00:01 blood 960 #> 1920 46.6 12 1828 1828-12-01 12:00:01 bone 960 #> 1921 43.0 1 1829 1829-01-01 00:00:00 blood 961 #> 1922 43.0 1 1829 1829-01-01 00:00:00 bone 961 #> 1923 49.4 2 1829 1829-01-31 10:00:00 blood 962 #> 1924 49.4 2 1829 1829-01-31 10:00:00 bone 962 #> 1925 72.3 3 1829 1829-03-02 20:00:01 blood 963 #> 1926 72.3 3 1829 1829-03-02 20:00:01 bone 963 #> 1927 95.0 4 1829 1829-04-02 06:00:00 blood 964 #> 1928 95.0 4 1829 1829-04-02 06:00:00 bone 964 #> 1929 67.5 5 1829 1829-05-02 16:00:00 blood 965 #> 1930 67.5 5 1829 1829-05-02 16:00:00 bone 965 #> 1931 73.9 6 1829 1829-06-02 02:00:01 blood 966 #> 1932 73.9 6 1829 1829-06-02 02:00:01 bone 966 #> 1933 90.8 7 1829 1829-07-02 12:00:00 blood 967 #> 1934 90.8 7 1829 1829-07-02 12:00:00 bone 967 #> 1935 78.3 8 1829 1829-08-01 22:00:00 blood 968 #> 1936 78.3 8 1829 1829-08-01 22:00:00 bone 968 #> 1937 52.8 9 1829 1829-09-01 08:00:01 blood 969 #> 1938 52.8 9 1829 1829-09-01 08:00:01 bone 969 #> 1939 57.2 10 1829 1829-10-01 18:00:00 blood 970 #> 1940 57.2 10 1829 1829-10-01 18:00:00 bone 970 #> 1941 67.6 11 1829 1829-11-01 04:00:00 blood 971 #> 1942 67.6 11 1829 1829-11-01 04:00:00 bone 971 #> 1943 56.5 12 1829 1829-12-01 14:00:01 blood 972 #> 1944 56.5 12 1829 1829-12-01 14:00:01 bone 972 #> 1945 52.2 1 1830 1830-01-01 00:00:00 blood 973 #> 1946 52.2 1 1830 1830-01-01 00:00:00 bone 973 #> 1947 72.1 2 1830 1830-01-31 10:00:00 blood 974 #> 1948 72.1 2 1830 1830-01-31 10:00:00 bone 974 #> 1949 84.6 3 1830 1830-03-02 20:00:01 blood 975 #> 1950 84.6 3 1830 1830-03-02 20:00:01 bone 975 #> 1951 107.1 4 1830 1830-04-02 06:00:00 blood 976 #> 1952 107.1 4 1830 1830-04-02 06:00:00 bone 976 #> 1953 66.3 5 1830 1830-05-02 16:00:00 blood 977 #> 1954 66.3 5 1830 1830-05-02 16:00:00 bone 977 #> 1955 65.1 6 1830 1830-06-02 02:00:01 blood 978 #> 1956 65.1 6 1830 1830-06-02 02:00:01 bone 978 #> 1957 43.9 7 1830 1830-07-02 12:00:00 blood 979 #> 1958 43.9 7 1830 1830-07-02 12:00:00 bone 979 #> 1959 50.7 8 1830 1830-08-01 22:00:00 blood 980 #> 1960 50.7 8 1830 1830-08-01 22:00:00 bone 980 #> 1961 62.1 9 1830 1830-09-01 08:00:01 blood 981 #> 1962 62.1 9 1830 1830-09-01 08:00:01 bone 981 #> 1963 84.4 10 1830 1830-10-01 18:00:00 blood 982 #> 1964 84.4 10 1830 1830-10-01 18:00:00 bone 982 #> 1965 81.2 11 1830 1830-11-01 04:00:00 blood 983 #> 1966 81.2 11 1830 1830-11-01 04:00:00 bone 983 #> 1967 82.1 12 1830 1830-12-01 14:00:01 blood 984 #> 1968 82.1 12 1830 1830-12-01 14:00:01 bone 984 #> 1969 47.5 1 1831 1831-01-01 00:00:00 blood 985 #> 1970 47.5 1 1831 1831-01-01 00:00:00 bone 985 #> 1971 50.1 2 1831 1831-01-31 10:00:00 blood 986 #> 1972 50.1 2 1831 1831-01-31 10:00:00 bone 986 #> 1973 93.4 3 1831 1831-03-02 20:00:01 blood 987 #> 1974 93.4 3 1831 1831-03-02 20:00:01 bone 987 #> 1975 54.6 4 1831 1831-04-02 06:00:00 blood 988 #> 1976 54.6 4 1831 1831-04-02 06:00:00 bone 988 #> 1977 38.1 5 1831 1831-05-02 16:00:00 blood 989 #> 1978 38.1 5 1831 1831-05-02 16:00:00 bone 989 #> 1979 33.4 6 1831 1831-06-02 02:00:01 blood 990 #> 1980 33.4 6 1831 1831-06-02 02:00:01 bone 990 #> 1981 45.2 7 1831 1831-07-02 12:00:00 blood 991 #> 1982 45.2 7 1831 1831-07-02 12:00:00 bone 991 #> 1983 54.9 8 1831 1831-08-01 22:00:00 blood 992 #> 1984 54.9 8 1831 1831-08-01 22:00:00 bone 992 #> 1985 37.9 9 1831 1831-09-01 08:00:01 blood 993 #> 1986 37.9 9 1831 1831-09-01 08:00:01 bone 993 #> 1987 46.2 10 1831 1831-10-01 18:00:00 blood 994 #> 1988 46.2 10 1831 1831-10-01 18:00:00 bone 994 #> 1989 43.5 11 1831 1831-11-01 04:00:00 blood 995 #> 1990 43.5 11 1831 1831-11-01 04:00:00 bone 995 #> 1991 28.9 12 1831 1831-12-01 14:00:01 blood 996 #> 1992 28.9 12 1831 1831-12-01 14:00:01 bone 996 #> 1993 30.9 1 1832 1832-01-01 00:00:00 blood 997 #> 1994 30.9 1 1832 1832-01-01 00:00:00 bone 997 #> 1995 55.5 2 1832 1832-01-31 12:00:00 blood 998 #> 1996 55.5 2 1832 1832-01-31 12:00:00 bone 998 #> 1997 55.1 3 1832 1832-03-02 00:00:01 blood 999 #> 1998 55.1 3 1832 1832-03-02 00:00:01 bone 999 #> 1999 26.9 4 1832 1832-04-01 12:00:00 blood 1000 #> 2000 26.9 4 1832 1832-04-01 12:00:00 bone 1000 #> 2001 41.3 5 1832 1832-05-02 00:00:00 blood 1001 #> 2002 41.3 5 1832 1832-05-02 00:00:00 bone 1001 #> 2003 26.7 6 1832 1832-06-01 12:00:01 blood 1002 #> 2004 26.7 6 1832 1832-06-01 12:00:01 bone 1002 #> 2005 13.9 7 1832 1832-07-02 00:00:00 blood 1003 #> 2006 13.9 7 1832 1832-07-02 00:00:00 bone 1003 #> 2007 8.9 8 1832 1832-08-01 12:00:00 blood 1004 #> 2008 8.9 8 1832 1832-08-01 12:00:00 bone 1004 #> 2009 8.2 9 1832 1832-09-01 00:00:01 blood 1005 #> 2010 8.2 9 1832 1832-09-01 00:00:01 bone 1005 #> 2011 21.1 10 1832 1832-10-01 12:00:00 blood 1006 #> 2012 21.1 10 1832 1832-10-01 12:00:00 bone 1006 #> 2013 14.3 11 1832 1832-11-01 00:00:00 blood 1007 #> 2014 14.3 11 1832 1832-11-01 00:00:00 bone 1007 #> 2015 27.5 12 1832 1832-12-01 12:00:01 blood 1008 #> 2016 27.5 12 1832 1832-12-01 12:00:01 bone 1008 #> 2017 11.3 1 1833 1833-01-01 00:00:00 blood 1009 #> 2018 11.3 1 1833 1833-01-01 00:00:00 bone 1009 #> 2019 14.9 2 1833 1833-01-31 10:00:00 blood 1010 #> 2020 14.9 2 1833 1833-01-31 10:00:00 bone 1010 #> 2021 11.8 3 1833 1833-03-02 20:00:01 blood 1011 #> 2022 11.8 3 1833 1833-03-02 20:00:01 bone 1011 #> 2023 2.8 4 1833 1833-04-02 06:00:00 blood 1012 #> 2024 2.8 4 1833 1833-04-02 06:00:00 bone 1012 #> 2025 12.9 5 1833 1833-05-02 16:00:00 blood 1013 #> 2026 12.9 5 1833 1833-05-02 16:00:00 bone 1013 #> 2027 1.0 6 1833 1833-06-02 02:00:01 blood 1014 #> 2028 1.0 6 1833 1833-06-02 02:00:01 bone 1014 #> 2029 7.0 7 1833 1833-07-02 12:00:00 blood 1015 #> 2030 7.0 7 1833 1833-07-02 12:00:00 bone 1015 #> 2031 5.7 8 1833 1833-08-01 22:00:00 blood 1016 #> 2032 5.7 8 1833 1833-08-01 22:00:00 bone 1016 #> 2033 11.6 9 1833 1833-09-01 08:00:01 blood 1017 #> 2034 11.6 9 1833 1833-09-01 08:00:01 bone 1017 #> 2035 7.5 10 1833 1833-10-01 18:00:00 blood 1018 #> 2036 7.5 10 1833 1833-10-01 18:00:00 bone 1018 #> 2037 5.9 11 1833 1833-11-01 04:00:00 blood 1019 #> 2038 5.9 11 1833 1833-11-01 04:00:00 bone 1019 #> 2039 9.9 12 1833 1833-12-01 14:00:01 blood 1020 #> 2040 9.9 12 1833 1833-12-01 14:00:01 bone 1020 #> 2041 4.9 1 1834 1834-01-01 00:00:00 blood 1021 #> 2042 4.9 1 1834 1834-01-01 00:00:00 bone 1021 #> 2043 18.1 2 1834 1834-01-31 10:00:00 blood 1022 #> 2044 18.1 2 1834 1834-01-31 10:00:00 bone 1022 #> 2045 3.9 3 1834 1834-03-02 20:00:01 blood 1023 #> 2046 3.9 3 1834 1834-03-02 20:00:01 bone 1023 #> 2047 1.4 4 1834 1834-04-02 06:00:00 blood 1024 #> 2048 1.4 4 1834 1834-04-02 06:00:00 bone 1024 #> 2049 8.8 5 1834 1834-05-02 16:00:00 blood 1025 #> 2050 8.8 5 1834 1834-05-02 16:00:00 bone 1025 #> 2051 7.8 6 1834 1834-06-02 02:00:01 blood 1026 #> 2052 7.8 6 1834 1834-06-02 02:00:01 bone 1026 #> 2053 8.7 7 1834 1834-07-02 12:00:00 blood 1027 #> 2054 8.7 7 1834 1834-07-02 12:00:00 bone 1027 #> 2055 4.0 8 1834 1834-08-01 22:00:00 blood 1028 #> 2056 4.0 8 1834 1834-08-01 22:00:00 bone 1028 #> 2057 11.5 9 1834 1834-09-01 08:00:01 blood 1029 #> 2058 11.5 9 1834 1834-09-01 08:00:01 bone 1029 #> 2059 24.8 10 1834 1834-10-01 18:00:00 blood 1030 #> 2060 24.8 10 1834 1834-10-01 18:00:00 bone 1030 #> 2061 30.5 11 1834 1834-11-01 04:00:00 blood 1031 #> 2062 30.5 11 1834 1834-11-01 04:00:00 bone 1031 #> 2063 34.5 12 1834 1834-12-01 14:00:01 blood 1032 #> 2064 34.5 12 1834 1834-12-01 14:00:01 bone 1032 #> 2065 7.5 1 1835 1835-01-01 00:00:00 blood 1033 #> 2066 7.5 1 1835 1835-01-01 00:00:00 bone 1033 #> 2067 24.5 2 1835 1835-01-31 10:00:00 blood 1034 #> 2068 24.5 2 1835 1835-01-31 10:00:00 bone 1034 #> 2069 19.7 3 1835 1835-03-02 20:00:01 blood 1035 #> 2070 19.7 3 1835 1835-03-02 20:00:01 bone 1035 #> 2071 61.5 4 1835 1835-04-02 06:00:00 blood 1036 #> 2072 61.5 4 1835 1835-04-02 06:00:00 bone 1036 #> 2073 43.6 5 1835 1835-05-02 16:00:00 blood 1037 #> 2074 43.6 5 1835 1835-05-02 16:00:00 bone 1037 #> 2075 33.2 6 1835 1835-06-02 02:00:01 blood 1038 #> 2076 33.2 6 1835 1835-06-02 02:00:01 bone 1038 #> 2077 59.8 7 1835 1835-07-02 12:00:00 blood 1039 #> 2078 59.8 7 1835 1835-07-02 12:00:00 bone 1039 #> 2079 59.0 8 1835 1835-08-01 22:00:00 blood 1040 #> 2080 59.0 8 1835 1835-08-01 22:00:00 bone 1040 #> 2081 100.8 9 1835 1835-09-01 08:00:01 blood 1041 #> 2082 100.8 9 1835 1835-09-01 08:00:01 bone 1041 #> 2083 95.2 10 1835 1835-10-01 18:00:00 blood 1042 #> 2084 95.2 10 1835 1835-10-01 18:00:00 bone 1042 #> 2085 100.0 11 1835 1835-11-01 04:00:00 blood 1043 #> 2086 100.0 11 1835 1835-11-01 04:00:00 bone 1043 #> 2087 77.5 12 1835 1835-12-01 14:00:01 blood 1044 #> 2088 77.5 12 1835 1835-12-01 14:00:01 bone 1044 #> 2089 88.6 1 1836 1836-01-01 00:00:00 blood 1045 #> 2090 88.6 1 1836 1836-01-01 00:00:00 bone 1045 #> 2091 107.6 2 1836 1836-01-31 12:00:00 blood 1046 #> 2092 107.6 2 1836 1836-01-31 12:00:00 bone 1046 #> 2093 98.1 3 1836 1836-03-02 00:00:01 blood 1047 #> 2094 98.1 3 1836 1836-03-02 00:00:01 bone 1047 #> 2095 142.9 4 1836 1836-04-01 12:00:00 blood 1048 #> 2096 142.9 4 1836 1836-04-01 12:00:00 bone 1048 #> 2097 111.4 5 1836 1836-05-02 00:00:00 blood 1049 #> 2098 111.4 5 1836 1836-05-02 00:00:00 bone 1049 #> 2099 124.7 6 1836 1836-06-01 12:00:01 blood 1050 #> 2100 124.7 6 1836 1836-06-01 12:00:01 bone 1050 #> 2101 116.7 7 1836 1836-07-02 00:00:00 blood 1051 #> 2102 116.7 7 1836 1836-07-02 00:00:00 bone 1051 #> 2103 107.8 8 1836 1836-08-01 12:00:00 blood 1052 #> 2104 107.8 8 1836 1836-08-01 12:00:00 bone 1052 #> 2105 95.1 9 1836 1836-09-01 00:00:01 blood 1053 #> 2106 95.1 9 1836 1836-09-01 00:00:01 bone 1053 #> 2107 137.4 10 1836 1836-10-01 12:00:00 blood 1054 #> 2108 137.4 10 1836 1836-10-01 12:00:00 bone 1054 #> 2109 120.9 11 1836 1836-11-01 00:00:00 blood 1055 #> 2110 120.9 11 1836 1836-11-01 00:00:00 bone 1055 #> 2111 206.2 12 1836 1836-12-01 12:00:01 blood 1056 #> 2112 206.2 12 1836 1836-12-01 12:00:01 bone 1056 #> 2113 188.0 1 1837 1837-01-01 00:00:00 blood 1057 #> 2114 188.0 1 1837 1837-01-01 00:00:00 bone 1057 #> 2115 175.6 2 1837 1837-01-31 10:00:00 blood 1058 #> 2116 175.6 2 1837 1837-01-31 10:00:00 bone 1058 #> 2117 134.6 3 1837 1837-03-02 20:00:01 blood 1059 #> 2118 134.6 3 1837 1837-03-02 20:00:01 bone 1059 #> 2119 138.2 4 1837 1837-04-02 06:00:00 blood 1060 #> 2120 138.2 4 1837 1837-04-02 06:00:00 bone 1060 #> 2121 111.3 5 1837 1837-05-02 16:00:00 blood 1061 #> 2122 111.3 5 1837 1837-05-02 16:00:00 bone 1061 #> 2123 158.0 6 1837 1837-06-02 02:00:01 blood 1062 #> 2124 158.0 6 1837 1837-06-02 02:00:01 bone 1062 #> 2125 162.8 7 1837 1837-07-02 12:00:00 blood 1063 #> 2126 162.8 7 1837 1837-07-02 12:00:00 bone 1063 #> 2127 134.0 8 1837 1837-08-01 22:00:00 blood 1064 #> 2128 134.0 8 1837 1837-08-01 22:00:00 bone 1064 #> 2129 96.3 9 1837 1837-09-01 08:00:01 blood 1065 #> 2130 96.3 9 1837 1837-09-01 08:00:01 bone 1065 #> 2131 123.7 10 1837 1837-10-01 18:00:00 blood 1066 #> 2132 123.7 10 1837 1837-10-01 18:00:00 bone 1066 #> 2133 107.0 11 1837 1837-11-01 04:00:00 blood 1067 #> 2134 107.0 11 1837 1837-11-01 04:00:00 bone 1067 #> 2135 129.8 12 1837 1837-12-01 14:00:01 blood 1068 #> 2136 129.8 12 1837 1837-12-01 14:00:01 bone 1068 #> 2137 144.9 1 1838 1838-01-01 00:00:00 blood 1069 #> 2138 144.9 1 1838 1838-01-01 00:00:00 bone 1069 #> 2139 84.8 2 1838 1838-01-31 10:00:00 blood 1070 #> 2140 84.8 2 1838 1838-01-31 10:00:00 bone 1070 #> 2141 140.8 3 1838 1838-03-02 20:00:01 blood 1071 #> 2142 140.8 3 1838 1838-03-02 20:00:01 bone 1071 #> 2143 126.6 4 1838 1838-04-02 06:00:00 blood 1072 #> 2144 126.6 4 1838 1838-04-02 06:00:00 bone 1072 #> 2145 137.6 5 1838 1838-05-02 16:00:00 blood 1073 #> 2146 137.6 5 1838 1838-05-02 16:00:00 bone 1073 #> 2147 94.5 6 1838 1838-06-02 02:00:01 blood 1074 #> 2148 94.5 6 1838 1838-06-02 02:00:01 bone 1074 #> 2149 108.2 7 1838 1838-07-02 12:00:00 blood 1075 #> 2150 108.2 7 1838 1838-07-02 12:00:00 bone 1075 #> 2151 78.8 8 1838 1838-08-01 22:00:00 blood 1076 #> 2152 78.8 8 1838 1838-08-01 22:00:00 bone 1076 #> 2153 73.6 9 1838 1838-09-01 08:00:01 blood 1077 #> 2154 73.6 9 1838 1838-09-01 08:00:01 bone 1077 #> 2155 90.8 10 1838 1838-10-01 18:00:00 blood 1078 #> 2156 90.8 10 1838 1838-10-01 18:00:00 bone 1078 #> 2157 77.4 11 1838 1838-11-01 04:00:00 blood 1079 #> 2158 77.4 11 1838 1838-11-01 04:00:00 bone 1079 #> 2159 79.8 12 1838 1838-12-01 14:00:01 blood 1080 #> 2160 79.8 12 1838 1838-12-01 14:00:01 bone 1080 #> 2161 107.6 1 1839 1839-01-01 00:00:00 blood 1081 #> 2162 107.6 1 1839 1839-01-01 00:00:00 bone 1081 #> 2163 102.5 2 1839 1839-01-31 10:00:00 blood 1082 #> 2164 102.5 2 1839 1839-01-31 10:00:00 bone 1082 #> 2165 77.7 3 1839 1839-03-02 20:00:01 blood 1083 #> 2166 77.7 3 1839 1839-03-02 20:00:01 bone 1083 #> 2167 61.8 4 1839 1839-04-02 06:00:00 blood 1084 #> 2168 61.8 4 1839 1839-04-02 06:00:00 bone 1084 #> 2169 53.8 5 1839 1839-05-02 16:00:00 blood 1085 #> 2170 53.8 5 1839 1839-05-02 16:00:00 bone 1085 #> 2171 54.6 6 1839 1839-06-02 02:00:01 blood 1086 #> 2172 54.6 6 1839 1839-06-02 02:00:01 bone 1086 #> 2173 84.7 7 1839 1839-07-02 12:00:00 blood 1087 #> 2174 84.7 7 1839 1839-07-02 12:00:00 bone 1087 #> 2175 131.2 8 1839 1839-08-01 22:00:00 blood 1088 #> 2176 131.2 8 1839 1839-08-01 22:00:00 bone 1088 #> 2177 132.7 9 1839 1839-09-01 08:00:01 blood 1089 #> 2178 132.7 9 1839 1839-09-01 08:00:01 bone 1089 #> 2179 90.8 10 1839 1839-10-01 18:00:00 blood 1090 #> 2180 90.8 10 1839 1839-10-01 18:00:00 bone 1090 #> 2181 68.8 11 1839 1839-11-01 04:00:00 blood 1091 #> 2182 68.8 11 1839 1839-11-01 04:00:00 bone 1091 #> 2183 63.6 12 1839 1839-12-01 14:00:01 blood 1092 #> 2184 63.6 12 1839 1839-12-01 14:00:01 bone 1092 #> 2185 81.2 1 1840 1840-01-01 00:00:00 blood 1093 #> 2186 81.2 1 1840 1840-01-01 00:00:00 bone 1093 #> 2187 87.7 2 1840 1840-01-31 12:00:00 blood 1094 #> 2188 87.7 2 1840 1840-01-31 12:00:00 bone 1094 #> 2189 55.5 3 1840 1840-03-02 00:00:01 blood 1095 #> 2190 55.5 3 1840 1840-03-02 00:00:01 bone 1095 #> 2191 65.9 4 1840 1840-04-01 12:00:00 blood 1096 #> 2192 65.9 4 1840 1840-04-01 12:00:00 bone 1096 #> 2193 69.2 5 1840 1840-05-02 00:00:00 blood 1097 #> 2194 69.2 5 1840 1840-05-02 00:00:00 bone 1097 #> 2195 48.5 6 1840 1840-06-01 12:00:01 blood 1098 #> 2196 48.5 6 1840 1840-06-01 12:00:01 bone 1098 #> 2197 60.7 7 1840 1840-07-02 00:00:00 blood 1099 #> 2198 60.7 7 1840 1840-07-02 00:00:00 bone 1099 #> 2199 57.8 8 1840 1840-08-01 12:00:00 blood 1100 #> 2200 57.8 8 1840 1840-08-01 12:00:00 bone 1100 #> 2201 74.0 9 1840 1840-09-01 00:00:01 blood 1101 #> 2202 74.0 9 1840 1840-09-01 00:00:01 bone 1101 #> 2203 49.8 10 1840 1840-10-01 12:00:00 blood 1102 #> 2204 49.8 10 1840 1840-10-01 12:00:00 bone 1102 #> 2205 54.3 11 1840 1840-11-01 00:00:00 blood 1103 #> 2206 54.3 11 1840 1840-11-01 00:00:00 bone 1103 #> 2207 53.7 12 1840 1840-12-01 12:00:01 blood 1104 #> 2208 53.7 12 1840 1840-12-01 12:00:01 bone 1104 #> 2209 24.0 1 1841 1841-01-01 00:00:00 blood 1105 #> 2210 24.0 1 1841 1841-01-01 00:00:00 bone 1105 #> 2211 29.9 2 1841 1841-01-31 10:00:00 blood 1106 #> 2212 29.9 2 1841 1841-01-31 10:00:00 bone 1106 #> 2213 29.7 3 1841 1841-03-02 20:00:01 blood 1107 #> 2214 29.7 3 1841 1841-03-02 20:00:01 bone 1107 #> 2215 42.6 4 1841 1841-04-02 06:00:00 blood 1108 #> 2216 42.6 4 1841 1841-04-02 06:00:00 bone 1108 #> 2217 67.4 5 1841 1841-05-02 16:00:00 blood 1109 #> 2218 67.4 5 1841 1841-05-02 16:00:00 bone 1109 #> 2219 55.7 6 1841 1841-06-02 02:00:01 blood 1110 #> 2220 55.7 6 1841 1841-06-02 02:00:01 bone 1110 #> 2221 30.8 7 1841 1841-07-02 12:00:00 blood 1111 #> 2222 30.8 7 1841 1841-07-02 12:00:00 bone 1111 #> 2223 39.3 8 1841 1841-08-01 22:00:00 blood 1112 #> 2224 39.3 8 1841 1841-08-01 22:00:00 bone 1112 #> 2225 35.1 9 1841 1841-09-01 08:00:01 blood 1113 #> 2226 35.1 9 1841 1841-09-01 08:00:01 bone 1113 #> 2227 28.5 10 1841 1841-10-01 18:00:00 blood 1114 #> 2228 28.5 10 1841 1841-10-01 18:00:00 bone 1114 #> 2229 19.8 11 1841 1841-11-01 04:00:00 blood 1115 #> 2230 19.8 11 1841 1841-11-01 04:00:00 bone 1115 #> 2231 38.8 12 1841 1841-12-01 14:00:01 blood 1116 #> 2232 38.8 12 1841 1841-12-01 14:00:01 bone 1116 #> 2233 20.4 1 1842 1842-01-01 00:00:00 blood 1117 #> 2234 20.4 1 1842 1842-01-01 00:00:00 bone 1117 #> 2235 22.1 2 1842 1842-01-31 10:00:00 blood 1118 #> 2236 22.1 2 1842 1842-01-31 10:00:00 bone 1118 #> 2237 21.7 3 1842 1842-03-02 20:00:01 blood 1119 #> 2238 21.7 3 1842 1842-03-02 20:00:01 bone 1119 #> 2239 26.9 4 1842 1842-04-02 06:00:00 blood 1120 #> 2240 26.9 4 1842 1842-04-02 06:00:00 bone 1120 #> 2241 24.9 5 1842 1842-05-02 16:00:00 blood 1121 #> 2242 24.9 5 1842 1842-05-02 16:00:00 bone 1121 #> 2243 20.5 6 1842 1842-06-02 02:00:01 blood 1122 #> 2244 20.5 6 1842 1842-06-02 02:00:01 bone 1122 #> 2245 12.6 7 1842 1842-07-02 12:00:00 blood 1123 #> 2246 12.6 7 1842 1842-07-02 12:00:00 bone 1123 #> 2247 26.5 8 1842 1842-08-01 22:00:00 blood 1124 #> 2248 26.5 8 1842 1842-08-01 22:00:00 bone 1124 #> 2249 18.5 9 1842 1842-09-01 08:00:01 blood 1125 #> 2250 18.5 9 1842 1842-09-01 08:00:01 bone 1125 #> 2251 38.1 10 1842 1842-10-01 18:00:00 blood 1126 #> 2252 38.1 10 1842 1842-10-01 18:00:00 bone 1126 #> 2253 40.5 11 1842 1842-11-01 04:00:00 blood 1127 #> 2254 40.5 11 1842 1842-11-01 04:00:00 bone 1127 #> 2255 17.6 12 1842 1842-12-01 14:00:01 blood 1128 #> 2256 17.6 12 1842 1842-12-01 14:00:01 bone 1128 #> 2257 13.3 1 1843 1843-01-01 00:00:00 blood 1129 #> 2258 13.3 1 1843 1843-01-01 00:00:00 bone 1129 #> 2259 3.5 2 1843 1843-01-31 10:00:00 blood 1130 #> 2260 3.5 2 1843 1843-01-31 10:00:00 bone 1130 #> 2261 8.3 3 1843 1843-03-02 20:00:01 blood 1131 #> 2262 8.3 3 1843 1843-03-02 20:00:01 bone 1131 #> 2263 8.8 4 1843 1843-04-02 06:00:00 blood 1132 #> 2264 8.8 4 1843 1843-04-02 06:00:00 bone 1132 #> 2265 21.1 5 1843 1843-05-02 16:00:00 blood 1133 #> 2266 21.1 5 1843 1843-05-02 16:00:00 bone 1133 #> 2267 10.5 6 1843 1843-06-02 02:00:01 blood 1134 #> 2268 10.5 6 1843 1843-06-02 02:00:01 bone 1134 #> 2269 9.5 7 1843 1843-07-02 12:00:00 blood 1135 #> 2270 9.5 7 1843 1843-07-02 12:00:00 bone 1135 #> 2271 11.8 8 1843 1843-08-01 22:00:00 blood 1136 #> 2272 11.8 8 1843 1843-08-01 22:00:00 bone 1136 #> 2273 4.2 9 1843 1843-09-01 08:00:01 blood 1137 #> 2274 4.2 9 1843 1843-09-01 08:00:01 bone 1137 #> 2275 5.3 10 1843 1843-10-01 18:00:00 blood 1138 #> 2276 5.3 10 1843 1843-10-01 18:00:00 bone 1138 #> 2277 19.1 11 1843 1843-11-01 04:00:00 blood 1139 #> 2278 19.1 11 1843 1843-11-01 04:00:00 bone 1139 #> 2279 12.7 12 1843 1843-12-01 14:00:01 blood 1140 #> 2280 12.7 12 1843 1843-12-01 14:00:01 bone 1140 #> 2281 9.4 1 1844 1844-01-01 00:00:00 blood 1141 #> 2282 9.4 1 1844 1844-01-01 00:00:00 bone 1141 #> 2283 14.7 2 1844 1844-01-31 12:00:00 blood 1142 #> 2284 14.7 2 1844 1844-01-31 12:00:00 bone 1142 #> 2285 13.6 3 1844 1844-03-02 00:00:01 blood 1143 #> 2286 13.6 3 1844 1844-03-02 00:00:01 bone 1143 #> 2287 20.8 4 1844 1844-04-01 12:00:00 blood 1144 #> 2288 20.8 4 1844 1844-04-01 12:00:00 bone 1144 #> 2289 12.0 5 1844 1844-05-02 00:00:00 blood 1145 #> 2290 12.0 5 1844 1844-05-02 00:00:00 bone 1145 #> 2291 3.7 6 1844 1844-06-01 12:00:01 blood 1146 #> 2292 3.7 6 1844 1844-06-01 12:00:01 bone 1146 #> 2293 21.2 7 1844 1844-07-02 00:00:00 blood 1147 #> 2294 21.2 7 1844 1844-07-02 00:00:00 bone 1147 #> 2295 23.9 8 1844 1844-08-01 12:00:00 blood 1148 #> 2296 23.9 8 1844 1844-08-01 12:00:00 bone 1148 #> 2297 6.9 9 1844 1844-09-01 00:00:01 blood 1149 #> 2298 6.9 9 1844 1844-09-01 00:00:01 bone 1149 #> 2299 21.5 10 1844 1844-10-01 12:00:00 blood 1150 #> 2300 21.5 10 1844 1844-10-01 12:00:00 bone 1150 #> 2301 10.7 11 1844 1844-11-01 00:00:00 blood 1151 #> 2302 10.7 11 1844 1844-11-01 00:00:00 bone 1151 #> 2303 21.6 12 1844 1844-12-01 12:00:01 blood 1152 #> 2304 21.6 12 1844 1844-12-01 12:00:01 bone 1152 #> 2305 25.7 1 1845 1845-01-01 00:00:00 blood 1153 #> 2306 25.7 1 1845 1845-01-01 00:00:00 bone 1153 #> 2307 43.6 2 1845 1845-01-31 10:00:00 blood 1154 #> 2308 43.6 2 1845 1845-01-31 10:00:00 bone 1154 #> 2309 43.3 3 1845 1845-03-02 20:00:01 blood 1155 #> 2310 43.3 3 1845 1845-03-02 20:00:01 bone 1155 #> 2311 56.9 4 1845 1845-04-02 06:00:00 blood 1156 #> 2312 56.9 4 1845 1845-04-02 06:00:00 bone 1156 #> 2313 47.8 5 1845 1845-05-02 16:00:00 blood 1157 #> 2314 47.8 5 1845 1845-05-02 16:00:00 bone 1157 #> 2315 31.1 6 1845 1845-06-02 02:00:01 blood 1158 #> 2316 31.1 6 1845 1845-06-02 02:00:01 bone 1158 #> 2317 30.6 7 1845 1845-07-02 12:00:00 blood 1159 #> 2318 30.6 7 1845 1845-07-02 12:00:00 bone 1159 #> 2319 32.3 8 1845 1845-08-01 22:00:00 blood 1160 #> 2320 32.3 8 1845 1845-08-01 22:00:00 bone 1160 #> 2321 29.6 9 1845 1845-09-01 08:00:01 blood 1161 #> 2322 29.6 9 1845 1845-09-01 08:00:01 bone 1161 #> 2323 40.7 10 1845 1845-10-01 18:00:00 blood 1162 #> 2324 40.7 10 1845 1845-10-01 18:00:00 bone 1162 #> 2325 39.4 11 1845 1845-11-01 04:00:00 blood 1163 #> 2326 39.4 11 1845 1845-11-01 04:00:00 bone 1163 #> 2327 59.7 12 1845 1845-12-01 14:00:01 blood 1164 #> 2328 59.7 12 1845 1845-12-01 14:00:01 bone 1164 #> 2329 38.7 1 1846 1846-01-01 00:00:00 blood 1165 #> 2330 38.7 1 1846 1846-01-01 00:00:00 bone 1165 #> 2331 51.0 2 1846 1846-01-31 10:00:00 blood 1166 #> 2332 51.0 2 1846 1846-01-31 10:00:00 bone 1166 #> 2333 63.9 3 1846 1846-03-02 20:00:01 blood 1167 #> 2334 63.9 3 1846 1846-03-02 20:00:01 bone 1167 #> 2335 69.2 4 1846 1846-04-02 06:00:00 blood 1168 #> 2336 69.2 4 1846 1846-04-02 06:00:00 bone 1168 #> 2337 59.9 5 1846 1846-05-02 16:00:00 blood 1169 #> 2338 59.9 5 1846 1846-05-02 16:00:00 bone 1169 #> 2339 65.1 6 1846 1846-06-02 02:00:01 blood 1170 #> 2340 65.1 6 1846 1846-06-02 02:00:01 bone 1170 #> 2341 46.5 7 1846 1846-07-02 12:00:00 blood 1171 #> 2342 46.5 7 1846 1846-07-02 12:00:00 bone 1171 #> 2343 54.8 8 1846 1846-08-01 22:00:00 blood 1172 #> 2344 54.8 8 1846 1846-08-01 22:00:00 bone 1172 #> 2345 107.1 9 1846 1846-09-01 08:00:01 blood 1173 #> 2346 107.1 9 1846 1846-09-01 08:00:01 bone 1173 #> 2347 55.9 10 1846 1846-10-01 18:00:00 blood 1174 #> 2348 55.9 10 1846 1846-10-01 18:00:00 bone 1174 #> 2349 60.4 11 1846 1846-11-01 04:00:00 blood 1175 #> 2350 60.4 11 1846 1846-11-01 04:00:00 bone 1175 #> 2351 65.5 12 1846 1846-12-01 14:00:01 blood 1176 #> 2352 65.5 12 1846 1846-12-01 14:00:01 bone 1176 #> 2353 62.6 1 1847 1847-01-01 00:00:00 blood 1177 #> 2354 62.6 1 1847 1847-01-01 00:00:00 bone 1177 #> 2355 44.9 2 1847 1847-01-31 10:00:00 blood 1178 #> 2356 44.9 2 1847 1847-01-31 10:00:00 bone 1178 #> 2357 85.7 3 1847 1847-03-02 20:00:01 blood 1179 #> 2358 85.7 3 1847 1847-03-02 20:00:01 bone 1179 #> 2359 44.7 4 1847 1847-04-02 06:00:00 blood 1180 #> 2360 44.7 4 1847 1847-04-02 06:00:00 bone 1180 #> 2361 75.4 5 1847 1847-05-02 16:00:00 blood 1181 #> 2362 75.4 5 1847 1847-05-02 16:00:00 bone 1181 #> 2363 85.3 6 1847 1847-06-02 02:00:01 blood 1182 #> 2364 85.3 6 1847 1847-06-02 02:00:01 bone 1182 #> 2365 52.2 7 1847 1847-07-02 12:00:00 blood 1183 #> 2366 52.2 7 1847 1847-07-02 12:00:00 bone 1183 #> 2367 140.6 8 1847 1847-08-01 22:00:00 blood 1184 #> 2368 140.6 8 1847 1847-08-01 22:00:00 bone 1184 #> 2369 161.2 9 1847 1847-09-01 08:00:01 blood 1185 #> 2370 161.2 9 1847 1847-09-01 08:00:01 bone 1185 #> 2371 180.4 10 1847 1847-10-01 18:00:00 blood 1186 #> 2372 180.4 10 1847 1847-10-01 18:00:00 bone 1186 #> 2373 138.9 11 1847 1847-11-01 04:00:00 blood 1187 #> 2374 138.9 11 1847 1847-11-01 04:00:00 bone 1187 #> 2375 109.6 12 1847 1847-12-01 14:00:01 blood 1188 #> 2376 109.6 12 1847 1847-12-01 14:00:01 bone 1188 #> 2377 159.1 1 1848 1848-01-01 00:00:00 blood 1189 #> 2378 159.1 1 1848 1848-01-01 00:00:00 bone 1189 #> 2379 111.8 2 1848 1848-01-31 12:00:00 blood 1190 #> 2380 111.8 2 1848 1848-01-31 12:00:00 bone 1190 #> 2381 108.9 3 1848 1848-03-02 00:00:01 blood 1191 #> 2382 108.9 3 1848 1848-03-02 00:00:01 bone 1191 #> 2383 107.1 4 1848 1848-04-01 12:00:00 blood 1192 #> 2384 107.1 4 1848 1848-04-01 12:00:00 bone 1192 #> 2385 102.2 5 1848 1848-05-02 00:00:00 blood 1193 #> 2386 102.2 5 1848 1848-05-02 00:00:00 bone 1193 #> 2387 123.8 6 1848 1848-06-01 12:00:01 blood 1194 #> 2388 123.8 6 1848 1848-06-01 12:00:01 bone 1194 #> 2389 139.2 7 1848 1848-07-02 00:00:00 blood 1195 #> 2390 139.2 7 1848 1848-07-02 00:00:00 bone 1195 #> 2391 132.5 8 1848 1848-08-01 12:00:00 blood 1196 #> 2392 132.5 8 1848 1848-08-01 12:00:00 bone 1196 #> 2393 100.3 9 1848 1848-09-01 00:00:01 blood 1197 #> 2394 100.3 9 1848 1848-09-01 00:00:01 bone 1197 #> 2395 132.4 10 1848 1848-10-01 12:00:00 blood 1198 #> 2396 132.4 10 1848 1848-10-01 12:00:00 bone 1198 #> 2397 114.6 11 1848 1848-11-01 00:00:00 blood 1199 #> 2398 114.6 11 1848 1848-11-01 00:00:00 bone 1199 #> 2399 159.9 12 1848 1848-12-01 12:00:01 blood 1200 #> 2400 159.9 12 1848 1848-12-01 12:00:01 bone 1200 #> 2401 156.7 1 1849 1849-01-01 00:00:00 blood 1201 #> 2402 156.7 1 1849 1849-01-01 00:00:00 bone 1201 #> 2403 131.7 2 1849 1849-01-31 10:00:00 blood 1202 #> 2404 131.7 2 1849 1849-01-31 10:00:00 bone 1202 #> 2405 96.5 3 1849 1849-03-02 20:00:01 blood 1203 #> 2406 96.5 3 1849 1849-03-02 20:00:01 bone 1203 #> 2407 102.5 4 1849 1849-04-02 06:00:00 blood 1204 #> 2408 102.5 4 1849 1849-04-02 06:00:00 bone 1204 #> 2409 80.6 5 1849 1849-05-02 16:00:00 blood 1205 #> 2410 80.6 5 1849 1849-05-02 16:00:00 bone 1205 #> 2411 81.2 6 1849 1849-06-02 02:00:01 blood 1206 #> 2412 81.2 6 1849 1849-06-02 02:00:01 bone 1206 #> 2413 78.0 7 1849 1849-07-02 12:00:00 blood 1207 #> 2414 78.0 7 1849 1849-07-02 12:00:00 bone 1207 #> 2415 61.3 8 1849 1849-08-01 22:00:00 blood 1208 #> 2416 61.3 8 1849 1849-08-01 22:00:00 bone 1208 #> 2417 93.7 9 1849 1849-09-01 08:00:01 blood 1209 #> 2418 93.7 9 1849 1849-09-01 08:00:01 bone 1209 #> 2419 71.5 10 1849 1849-10-01 18:00:00 blood 1210 #> 2420 71.5 10 1849 1849-10-01 18:00:00 bone 1210 #> 2421 99.7 11 1849 1849-11-01 04:00:00 blood 1211 #> 2422 99.7 11 1849 1849-11-01 04:00:00 bone 1211 #> 2423 97.0 12 1849 1849-12-01 14:00:01 blood 1212 #> 2424 97.0 12 1849 1849-12-01 14:00:01 bone 1212 #> 2425 78.0 1 1850 1850-01-01 00:00:00 blood 1213 #> 2426 78.0 1 1850 1850-01-01 00:00:00 bone 1213 #> 2427 89.4 2 1850 1850-01-31 10:00:00 blood 1214 #> 2428 89.4 2 1850 1850-01-31 10:00:00 bone 1214 #> 2429 82.6 3 1850 1850-03-02 20:00:01 blood 1215 #> 2430 82.6 3 1850 1850-03-02 20:00:01 bone 1215 #> 2431 44.1 4 1850 1850-04-02 06:00:00 blood 1216 #> 2432 44.1 4 1850 1850-04-02 06:00:00 bone 1216 #> 2433 61.6 5 1850 1850-05-02 16:00:00 blood 1217 #> 2434 61.6 5 1850 1850-05-02 16:00:00 bone 1217 #> 2435 70.0 6 1850 1850-06-02 02:00:01 blood 1218 #> 2436 70.0 6 1850 1850-06-02 02:00:01 bone 1218 #> 2437 39.1 7 1850 1850-07-02 12:00:00 blood 1219 #> 2438 39.1 7 1850 1850-07-02 12:00:00 bone 1219 #> 2439 61.6 8 1850 1850-08-01 22:00:00 blood 1220 #> 2440 61.6 8 1850 1850-08-01 22:00:00 bone 1220 #> 2441 86.2 9 1850 1850-09-01 08:00:01 blood 1221 #> 2442 86.2 9 1850 1850-09-01 08:00:01 bone 1221 #> 2443 71.0 10 1850 1850-10-01 18:00:00 blood 1222 #> 2444 71.0 10 1850 1850-10-01 18:00:00 bone 1222 #> 2445 54.8 11 1850 1850-11-01 04:00:00 blood 1223 #> 2446 54.8 11 1850 1850-11-01 04:00:00 bone 1223 #> 2447 60.0 12 1850 1850-12-01 14:00:01 blood 1224 #> 2448 60.0 12 1850 1850-12-01 14:00:01 bone 1224 #> 2449 75.5 1 1851 1851-01-01 00:00:00 blood 1225 #> 2450 75.5 1 1851 1851-01-01 00:00:00 bone 1225 #> 2451 105.4 2 1851 1851-01-31 10:00:00 blood 1226 #> 2452 105.4 2 1851 1851-01-31 10:00:00 bone 1226 #> 2453 64.6 3 1851 1851-03-02 20:00:01 blood 1227 #> 2454 64.6 3 1851 1851-03-02 20:00:01 bone 1227 #> 2455 56.5 4 1851 1851-04-02 06:00:00 blood 1228 #> 2456 56.5 4 1851 1851-04-02 06:00:00 bone 1228 #> 2457 62.6 5 1851 1851-05-02 16:00:00 blood 1229 #> 2458 62.6 5 1851 1851-05-02 16:00:00 bone 1229 #> 2459 63.2 6 1851 1851-06-02 02:00:01 blood 1230 #> 2460 63.2 6 1851 1851-06-02 02:00:01 bone 1230 #> 2461 36.1 7 1851 1851-07-02 12:00:00 blood 1231 #> 2462 36.1 7 1851 1851-07-02 12:00:00 bone 1231 #> 2463 57.4 8 1851 1851-08-01 22:00:00 blood 1232 #> 2464 57.4 8 1851 1851-08-01 22:00:00 bone 1232 #> 2465 67.9 9 1851 1851-09-01 08:00:01 blood 1233 #> 2466 67.9 9 1851 1851-09-01 08:00:01 bone 1233 #> 2467 62.5 10 1851 1851-10-01 18:00:00 blood 1234 #> 2468 62.5 10 1851 1851-10-01 18:00:00 bone 1234 #> 2469 50.9 11 1851 1851-11-01 04:00:00 blood 1235 #> 2470 50.9 11 1851 1851-11-01 04:00:00 bone 1235 #> 2471 71.4 12 1851 1851-12-01 14:00:01 blood 1236 #> 2472 71.4 12 1851 1851-12-01 14:00:01 bone 1236 #> 2473 68.4 1 1852 1852-01-01 00:00:00 blood 1237 #> 2474 68.4 1 1852 1852-01-01 00:00:00 bone 1237 #> 2475 67.5 2 1852 1852-01-31 12:00:00 blood 1238 #> 2476 67.5 2 1852 1852-01-31 12:00:00 bone 1238 #> 2477 61.2 3 1852 1852-03-02 00:00:01 blood 1239 #> 2478 61.2 3 1852 1852-03-02 00:00:01 bone 1239 #> 2479 65.4 4 1852 1852-04-01 12:00:00 blood 1240 #> 2480 65.4 4 1852 1852-04-01 12:00:00 bone 1240 #> 2481 54.9 5 1852 1852-05-02 00:00:00 blood 1241 #> 2482 54.9 5 1852 1852-05-02 00:00:00 bone 1241 #> 2483 46.9 6 1852 1852-06-01 12:00:01 blood 1242 #> 2484 46.9 6 1852 1852-06-01 12:00:01 bone 1242 #> 2485 42.0 7 1852 1852-07-02 00:00:00 blood 1243 #> 2486 42.0 7 1852 1852-07-02 00:00:00 bone 1243 #> 2487 39.7 8 1852 1852-08-01 12:00:00 blood 1244 #> 2488 39.7 8 1852 1852-08-01 12:00:00 bone 1244 #> 2489 37.5 9 1852 1852-09-01 00:00:01 blood 1245 #> 2490 37.5 9 1852 1852-09-01 00:00:01 bone 1245 #> 2491 67.3 10 1852 1852-10-01 12:00:00 blood 1246 #> 2492 67.3 10 1852 1852-10-01 12:00:00 bone 1246 #> 2493 54.3 11 1852 1852-11-01 00:00:00 blood 1247 #> 2494 54.3 11 1852 1852-11-01 00:00:00 bone 1247 #> 2495 45.4 12 1852 1852-12-01 12:00:01 blood 1248 #> 2496 45.4 12 1852 1852-12-01 12:00:01 bone 1248 #> 2497 41.1 1 1853 1853-01-01 00:00:00 blood 1249 #> 2498 41.1 1 1853 1853-01-01 00:00:00 bone 1249 #> 2499 42.9 2 1853 1853-01-31 10:00:00 blood 1250 #> 2500 42.9 2 1853 1853-01-31 10:00:00 bone 1250 #> 2501 37.7 3 1853 1853-03-02 20:00:01 blood 1251 #> 2502 37.7 3 1853 1853-03-02 20:00:01 bone 1251 #> 2503 47.6 4 1853 1853-04-02 06:00:00 blood 1252 #> 2504 47.6 4 1853 1853-04-02 06:00:00 bone 1252 #> 2505 34.7 5 1853 1853-05-02 16:00:00 blood 1253 #> 2506 34.7 5 1853 1853-05-02 16:00:00 bone 1253 #> 2507 40.0 6 1853 1853-06-02 02:00:01 blood 1254 #> 2508 40.0 6 1853 1853-06-02 02:00:01 bone 1254 #> 2509 45.9 7 1853 1853-07-02 12:00:00 blood 1255 #> 2510 45.9 7 1853 1853-07-02 12:00:00 bone 1255 #> 2511 50.4 8 1853 1853-08-01 22:00:00 blood 1256 #> 2512 50.4 8 1853 1853-08-01 22:00:00 bone 1256 #> 2513 33.5 9 1853 1853-09-01 08:00:01 blood 1257 #> 2514 33.5 9 1853 1853-09-01 08:00:01 bone 1257 #> 2515 42.3 10 1853 1853-10-01 18:00:00 blood 1258 #> 2516 42.3 10 1853 1853-10-01 18:00:00 bone 1258 #> 2517 28.8 11 1853 1853-11-01 04:00:00 blood 1259 #> 2518 28.8 11 1853 1853-11-01 04:00:00 bone 1259 #> 2519 23.4 12 1853 1853-12-01 14:00:01 blood 1260 #> 2520 23.4 12 1853 1853-12-01 14:00:01 bone 1260 #> 2521 15.4 1 1854 1854-01-01 00:00:00 blood 1261 #> 2522 15.4 1 1854 1854-01-01 00:00:00 bone 1261 #> 2523 20.0 2 1854 1854-01-31 10:00:00 blood 1262 #> 2524 20.0 2 1854 1854-01-31 10:00:00 bone 1262 #> 2525 20.7 3 1854 1854-03-02 20:00:01 blood 1263 #> 2526 20.7 3 1854 1854-03-02 20:00:01 bone 1263 #> 2527 26.4 4 1854 1854-04-02 06:00:00 blood 1264 #> 2528 26.4 4 1854 1854-04-02 06:00:00 bone 1264 #> 2529 24.0 5 1854 1854-05-02 16:00:00 blood 1265 #> 2530 24.0 5 1854 1854-05-02 16:00:00 bone 1265 #> 2531 21.1 6 1854 1854-06-02 02:00:01 blood 1266 #> 2532 21.1 6 1854 1854-06-02 02:00:01 bone 1266 #> 2533 18.7 7 1854 1854-07-02 12:00:00 blood 1267 #> 2534 18.7 7 1854 1854-07-02 12:00:00 bone 1267 #> 2535 15.8 8 1854 1854-08-01 22:00:00 blood 1268 #> 2536 15.8 8 1854 1854-08-01 22:00:00 bone 1268 #> 2537 22.4 9 1854 1854-09-01 08:00:01 blood 1269 #> 2538 22.4 9 1854 1854-09-01 08:00:01 bone 1269 #> 2539 12.7 10 1854 1854-10-01 18:00:00 blood 1270 #> 2540 12.7 10 1854 1854-10-01 18:00:00 bone 1270 #> 2541 28.2 11 1854 1854-11-01 04:00:00 blood 1271 #> 2542 28.2 11 1854 1854-11-01 04:00:00 bone 1271 #> 2543 21.4 12 1854 1854-12-01 14:00:01 blood 1272 #> 2544 21.4 12 1854 1854-12-01 14:00:01 bone 1272 #> 2545 12.3 1 1855 1855-01-01 00:00:00 blood 1273 #> 2546 12.3 1 1855 1855-01-01 00:00:00 bone 1273 #> 2547 11.4 2 1855 1855-01-31 10:00:00 blood 1274 #> 2548 11.4 2 1855 1855-01-31 10:00:00 bone 1274 #> 2549 17.4 3 1855 1855-03-02 20:00:01 blood 1275 #> 2550 17.4 3 1855 1855-03-02 20:00:01 bone 1275 #> 2551 4.4 4 1855 1855-04-02 06:00:00 blood 1276 #> 2552 4.4 4 1855 1855-04-02 06:00:00 bone 1276 #> 2553 9.1 5 1855 1855-05-02 16:00:00 blood 1277 #> 2554 9.1 5 1855 1855-05-02 16:00:00 bone 1277 #> 2555 5.3 6 1855 1855-06-02 02:00:01 blood 1278 #> 2556 5.3 6 1855 1855-06-02 02:00:01 bone 1278 #> 2557 0.4 7 1855 1855-07-02 12:00:00 blood 1279 #> 2558 0.4 7 1855 1855-07-02 12:00:00 bone 1279 #> 2559 3.1 8 1855 1855-08-01 22:00:00 blood 1280 #> 2560 3.1 8 1855 1855-08-01 22:00:00 bone 1280 #> 2561 0.0 9 1855 1855-09-01 08:00:01 blood 1281 #> 2562 0.0 9 1855 1855-09-01 08:00:01 bone 1281 #> 2563 9.7 10 1855 1855-10-01 18:00:00 blood 1282 #> 2564 9.7 10 1855 1855-10-01 18:00:00 bone 1282 #> 2565 4.3 11 1855 1855-11-01 04:00:00 blood 1283 #> 2566 4.3 11 1855 1855-11-01 04:00:00 bone 1283 #> 2567 3.1 12 1855 1855-12-01 14:00:01 blood 1284 #> 2568 3.1 12 1855 1855-12-01 14:00:01 bone 1284 #> 2569 0.5 1 1856 1856-01-01 00:00:00 blood 1285 #> 2570 0.5 1 1856 1856-01-01 00:00:00 bone 1285 #> 2571 4.9 2 1856 1856-01-31 12:00:00 blood 1286 #> 2572 4.9 2 1856 1856-01-31 12:00:00 bone 1286 #> 2573 0.4 3 1856 1856-03-02 00:00:01 blood 1287 #> 2574 0.4 3 1856 1856-03-02 00:00:01 bone 1287 #> 2575 6.5 4 1856 1856-04-01 12:00:00 blood 1288 #> 2576 6.5 4 1856 1856-04-01 12:00:00 bone 1288 #> 2577 0.0 5 1856 1856-05-02 00:00:00 blood 1289 #> 2578 0.0 5 1856 1856-05-02 00:00:00 bone 1289 #> 2579 5.0 6 1856 1856-06-01 12:00:01 blood 1290 #> 2580 5.0 6 1856 1856-06-01 12:00:01 bone 1290 #> 2581 4.6 7 1856 1856-07-02 00:00:00 blood 1291 #> 2582 4.6 7 1856 1856-07-02 00:00:00 bone 1291 #> 2583 5.9 8 1856 1856-08-01 12:00:00 blood 1292 #> 2584 5.9 8 1856 1856-08-01 12:00:00 bone 1292 #> 2585 4.4 9 1856 1856-09-01 00:00:01 blood 1293 #> 2586 4.4 9 1856 1856-09-01 00:00:01 bone 1293 #> 2587 4.5 10 1856 1856-10-01 12:00:00 blood 1294 #> 2588 4.5 10 1856 1856-10-01 12:00:00 bone 1294 #> 2589 7.7 11 1856 1856-11-01 00:00:00 blood 1295 #> 2590 7.7 11 1856 1856-11-01 00:00:00 bone 1295 #> 2591 7.2 12 1856 1856-12-01 12:00:01 blood 1296 #> 2592 7.2 12 1856 1856-12-01 12:00:01 bone 1296 #> 2593 13.7 1 1857 1857-01-01 00:00:00 blood 1297 #> 2594 13.7 1 1857 1857-01-01 00:00:00 bone 1297 #> 2595 7.4 2 1857 1857-01-31 10:00:00 blood 1298 #> 2596 7.4 2 1857 1857-01-31 10:00:00 bone 1298 #> 2597 5.2 3 1857 1857-03-02 20:00:01 blood 1299 #> 2598 5.2 3 1857 1857-03-02 20:00:01 bone 1299 #> 2599 11.1 4 1857 1857-04-02 06:00:00 blood 1300 #> 2600 11.1 4 1857 1857-04-02 06:00:00 bone 1300 #> 2601 29.2 5 1857 1857-05-02 16:00:00 blood 1301 #> 2602 29.2 5 1857 1857-05-02 16:00:00 bone 1301 #> 2603 16.0 6 1857 1857-06-02 02:00:01 blood 1302 #> 2604 16.0 6 1857 1857-06-02 02:00:01 bone 1302 #> 2605 22.2 7 1857 1857-07-02 12:00:00 blood 1303 #> 2606 22.2 7 1857 1857-07-02 12:00:00 bone 1303 #> 2607 16.9 8 1857 1857-08-01 22:00:00 blood 1304 #> 2608 16.9 8 1857 1857-08-01 22:00:00 bone 1304 #> 2609 42.4 9 1857 1857-09-01 08:00:01 blood 1305 #> 2610 42.4 9 1857 1857-09-01 08:00:01 bone 1305 #> 2611 40.6 10 1857 1857-10-01 18:00:00 blood 1306 #> 2612 40.6 10 1857 1857-10-01 18:00:00 bone 1306 #> 2613 31.4 11 1857 1857-11-01 04:00:00 blood 1307 #> 2614 31.4 11 1857 1857-11-01 04:00:00 bone 1307 #> 2615 37.2 12 1857 1857-12-01 14:00:01 blood 1308 #> 2616 37.2 12 1857 1857-12-01 14:00:01 bone 1308 #> 2617 39.0 1 1858 1858-01-01 00:00:00 blood 1309 #> 2618 39.0 1 1858 1858-01-01 00:00:00 bone 1309 #> 2619 34.9 2 1858 1858-01-31 10:00:00 blood 1310 #> 2620 34.9 2 1858 1858-01-31 10:00:00 bone 1310 #> 2621 57.5 3 1858 1858-03-02 20:00:01 blood 1311 #> 2622 57.5 3 1858 1858-03-02 20:00:01 bone 1311 #> 2623 38.3 4 1858 1858-04-02 06:00:00 blood 1312 #> 2624 38.3 4 1858 1858-04-02 06:00:00 bone 1312 #> 2625 41.4 5 1858 1858-05-02 16:00:00 blood 1313 #> 2626 41.4 5 1858 1858-05-02 16:00:00 bone 1313 #> 2627 44.5 6 1858 1858-06-02 02:00:01 blood 1314 #> 2628 44.5 6 1858 1858-06-02 02:00:01 bone 1314 #> 2629 56.7 7 1858 1858-07-02 12:00:00 blood 1315 #> 2630 56.7 7 1858 1858-07-02 12:00:00 bone 1315 #> 2631 55.3 8 1858 1858-08-01 22:00:00 blood 1316 #> 2632 55.3 8 1858 1858-08-01 22:00:00 bone 1316 #> 2633 80.1 9 1858 1858-09-01 08:00:01 blood 1317 #> 2634 80.1 9 1858 1858-09-01 08:00:01 bone 1317 #> 2635 91.2 10 1858 1858-10-01 18:00:00 blood 1318 #> 2636 91.2 10 1858 1858-10-01 18:00:00 bone 1318 #> 2637 51.9 11 1858 1858-11-01 04:00:00 blood 1319 #> 2638 51.9 11 1858 1858-11-01 04:00:00 bone 1319 #> 2639 66.9 12 1858 1858-12-01 14:00:01 blood 1320 #> 2640 66.9 12 1858 1858-12-01 14:00:01 bone 1320 #> 2641 83.7 1 1859 1859-01-01 00:00:00 blood 1321 #> 2642 83.7 1 1859 1859-01-01 00:00:00 bone 1321 #> 2643 87.6 2 1859 1859-01-31 10:00:00 blood 1322 #> 2644 87.6 2 1859 1859-01-31 10:00:00 bone 1322 #> 2645 90.3 3 1859 1859-03-02 20:00:01 blood 1323 #> 2646 90.3 3 1859 1859-03-02 20:00:01 bone 1323 #> 2647 85.7 4 1859 1859-04-02 06:00:00 blood 1324 #> 2648 85.7 4 1859 1859-04-02 06:00:00 bone 1324 #> 2649 91.0 5 1859 1859-05-02 16:00:00 blood 1325 #> 2650 91.0 5 1859 1859-05-02 16:00:00 bone 1325 #> 2651 87.1 6 1859 1859-06-02 02:00:01 blood 1326 #> 2652 87.1 6 1859 1859-06-02 02:00:01 bone 1326 #> 2653 95.2 7 1859 1859-07-02 12:00:00 blood 1327 #> 2654 95.2 7 1859 1859-07-02 12:00:00 bone 1327 #> 2655 106.8 8 1859 1859-08-01 22:00:00 blood 1328 #> 2656 106.8 8 1859 1859-08-01 22:00:00 bone 1328 #> 2657 105.8 9 1859 1859-09-01 08:00:01 blood 1329 #> 2658 105.8 9 1859 1859-09-01 08:00:01 bone 1329 #> 2659 114.6 10 1859 1859-10-01 18:00:00 blood 1330 #> 2660 114.6 10 1859 1859-10-01 18:00:00 bone 1330 #> 2661 97.2 11 1859 1859-11-01 04:00:00 blood 1331 #> 2662 97.2 11 1859 1859-11-01 04:00:00 bone 1331 #> 2663 81.0 12 1859 1859-12-01 14:00:01 blood 1332 #> 2664 81.0 12 1859 1859-12-01 14:00:01 bone 1332 #> 2665 81.5 1 1860 1860-01-01 00:00:00 blood 1333 #> 2666 81.5 1 1860 1860-01-01 00:00:00 bone 1333 #> 2667 88.0 2 1860 1860-01-31 12:00:01 blood 1334 #> 2668 88.0 2 1860 1860-01-31 12:00:01 bone 1334 #> 2669 98.9 3 1860 1860-03-02 00:00:01 blood 1335 #> 2670 98.9 3 1860 1860-03-02 00:00:01 bone 1335 #> 2671 71.4 4 1860 1860-04-01 12:00:00 blood 1336 #> 2672 71.4 4 1860 1860-04-01 12:00:00 bone 1336 #> 2673 107.1 5 1860 1860-05-02 00:00:01 blood 1337 #> 2674 107.1 5 1860 1860-05-02 00:00:01 bone 1337 #> 2675 108.6 6 1860 1860-06-01 12:00:01 blood 1338 #> 2676 108.6 6 1860 1860-06-01 12:00:01 bone 1338 #> 2677 116.7 7 1860 1860-07-02 00:00:00 blood 1339 #> 2678 116.7 7 1860 1860-07-02 00:00:00 bone 1339 #> 2679 100.3 8 1860 1860-08-01 12:00:01 blood 1340 #> 2680 100.3 8 1860 1860-08-01 12:00:01 bone 1340 #> 2681 92.2 9 1860 1860-09-01 00:00:01 blood 1341 #> 2682 92.2 9 1860 1860-09-01 00:00:01 bone 1341 #> 2683 90.1 10 1860 1860-10-01 12:00:00 blood 1342 #> 2684 90.1 10 1860 1860-10-01 12:00:00 bone 1342 #> 2685 97.9 11 1860 1860-11-01 00:00:01 blood 1343 #> 2686 97.9 11 1860 1860-11-01 00:00:01 bone 1343 #> 2687 95.6 12 1860 1860-12-01 12:00:01 blood 1344 #> 2688 95.6 12 1860 1860-12-01 12:00:01 bone 1344 #> 2689 62.3 1 1861 1861-01-01 00:00:00 blood 1345 #> 2690 62.3 1 1861 1861-01-01 00:00:00 bone 1345 #> 2691 77.8 2 1861 1861-01-31 10:00:01 blood 1346 #> 2692 77.8 2 1861 1861-01-31 10:00:01 bone 1346 #> 2693 101.0 3 1861 1861-03-02 20:00:01 blood 1347 #> 2694 101.0 3 1861 1861-03-02 20:00:01 bone 1347 #> 2695 98.5 4 1861 1861-04-02 06:00:00 blood 1348 #> 2696 98.5 4 1861 1861-04-02 06:00:00 bone 1348 #> 2697 56.8 5 1861 1861-05-02 16:00:01 blood 1349 #> 2698 56.8 5 1861 1861-05-02 16:00:01 bone 1349 #> 2699 87.8 6 1861 1861-06-02 02:00:01 blood 1350 #> 2700 87.8 6 1861 1861-06-02 02:00:01 bone 1350 #> 2701 78.0 7 1861 1861-07-02 12:00:00 blood 1351 #> 2702 78.0 7 1861 1861-07-02 12:00:00 bone 1351 #> 2703 82.5 8 1861 1861-08-01 22:00:01 blood 1352 #> 2704 82.5 8 1861 1861-08-01 22:00:01 bone 1352 #> 2705 79.9 9 1861 1861-09-01 08:00:01 blood 1353 #> 2706 79.9 9 1861 1861-09-01 08:00:01 bone 1353 #> 2707 67.2 10 1861 1861-10-01 18:00:00 blood 1354 #> 2708 67.2 10 1861 1861-10-01 18:00:00 bone 1354 #> 2709 53.7 11 1861 1861-11-01 04:00:01 blood 1355 #> 2710 53.7 11 1861 1861-11-01 04:00:01 bone 1355 #> 2711 80.5 12 1861 1861-12-01 14:00:01 blood 1356 #> 2712 80.5 12 1861 1861-12-01 14:00:01 bone 1356 #> 2713 63.1 1 1862 1862-01-01 00:00:00 blood 1357 #> 2714 63.1 1 1862 1862-01-01 00:00:00 bone 1357 #> 2715 64.5 2 1862 1862-01-31 10:00:01 blood 1358 #> 2716 64.5 2 1862 1862-01-31 10:00:01 bone 1358 #> 2717 43.6 3 1862 1862-03-02 20:00:01 blood 1359 #> 2718 43.6 3 1862 1862-03-02 20:00:01 bone 1359 #> 2719 53.7 4 1862 1862-04-02 06:00:00 blood 1360 #> 2720 53.7 4 1862 1862-04-02 06:00:00 bone 1360 #> 2721 64.4 5 1862 1862-05-02 16:00:01 blood 1361 #> 2722 64.4 5 1862 1862-05-02 16:00:01 bone 1361 #> 2723 84.0 6 1862 1862-06-02 02:00:01 blood 1362 #> 2724 84.0 6 1862 1862-06-02 02:00:01 bone 1362 #> 2725 73.4 7 1862 1862-07-02 12:00:00 blood 1363 #> 2726 73.4 7 1862 1862-07-02 12:00:00 bone 1363 #> 2727 62.5 8 1862 1862-08-01 22:00:01 blood 1364 #> 2728 62.5 8 1862 1862-08-01 22:00:01 bone 1364 #> 2729 66.6 9 1862 1862-09-01 08:00:01 blood 1365 #> 2730 66.6 9 1862 1862-09-01 08:00:01 bone 1365 #> 2731 42.0 10 1862 1862-10-01 18:00:00 blood 1366 #> 2732 42.0 10 1862 1862-10-01 18:00:00 bone 1366 #> 2733 50.6 11 1862 1862-11-01 04:00:01 blood 1367 #> 2734 50.6 11 1862 1862-11-01 04:00:01 bone 1367 #> 2735 40.9 12 1862 1862-12-01 14:00:01 blood 1368 #> 2736 40.9 12 1862 1862-12-01 14:00:01 bone 1368 #> 2737 48.3 1 1863 1863-01-01 00:00:00 blood 1369 #> 2738 48.3 1 1863 1863-01-01 00:00:00 bone 1369 #> 2739 56.7 2 1863 1863-01-31 10:00:01 blood 1370 #> 2740 56.7 2 1863 1863-01-31 10:00:01 bone 1370 #> 2741 66.4 3 1863 1863-03-02 20:00:01 blood 1371 #> 2742 66.4 3 1863 1863-03-02 20:00:01 bone 1371 #> 2743 40.6 4 1863 1863-04-02 06:00:00 blood 1372 #> 2744 40.6 4 1863 1863-04-02 06:00:00 bone 1372 #> 2745 53.8 5 1863 1863-05-02 16:00:01 blood 1373 #> 2746 53.8 5 1863 1863-05-02 16:00:01 bone 1373 #> 2747 40.8 6 1863 1863-06-02 02:00:01 blood 1374 #> 2748 40.8 6 1863 1863-06-02 02:00:01 bone 1374 #> 2749 32.7 7 1863 1863-07-02 12:00:00 blood 1375 #> 2750 32.7 7 1863 1863-07-02 12:00:00 bone 1375 #> 2751 48.1 8 1863 1863-08-01 22:00:01 blood 1376 #> 2752 48.1 8 1863 1863-08-01 22:00:01 bone 1376 #> 2753 22.0 9 1863 1863-09-01 08:00:01 blood 1377 #> 2754 22.0 9 1863 1863-09-01 08:00:01 bone 1377 #> 2755 39.9 10 1863 1863-10-01 18:00:00 blood 1378 #> 2756 39.9 10 1863 1863-10-01 18:00:00 bone 1378 #> 2757 37.7 11 1863 1863-11-01 04:00:01 blood 1379 #> 2758 37.7 11 1863 1863-11-01 04:00:01 bone 1379 #> 2759 41.2 12 1863 1863-12-01 14:00:01 blood 1380 #> 2760 41.2 12 1863 1863-12-01 14:00:01 bone 1380 #> 2761 57.7 1 1864 1864-01-01 00:00:00 blood 1381 #> 2762 57.7 1 1864 1864-01-01 00:00:00 bone 1381 #> 2763 47.1 2 1864 1864-01-31 12:00:01 blood 1382 #> 2764 47.1 2 1864 1864-01-31 12:00:01 bone 1382 #> 2765 66.3 3 1864 1864-03-02 00:00:01 blood 1383 #> 2766 66.3 3 1864 1864-03-02 00:00:01 bone 1383 #> 2767 35.8 4 1864 1864-04-01 12:00:00 blood 1384 #> 2768 35.8 4 1864 1864-04-01 12:00:00 bone 1384 #> 2769 40.6 5 1864 1864-05-02 00:00:01 blood 1385 #> 2770 40.6 5 1864 1864-05-02 00:00:01 bone 1385 #> 2771 57.8 6 1864 1864-06-01 12:00:01 blood 1386 #> 2772 57.8 6 1864 1864-06-01 12:00:01 bone 1386 #> 2773 54.7 7 1864 1864-07-02 00:00:00 blood 1387 #> 2774 54.7 7 1864 1864-07-02 00:00:00 bone 1387 #> 2775 54.8 8 1864 1864-08-01 12:00:01 blood 1388 #> 2776 54.8 8 1864 1864-08-01 12:00:01 bone 1388 #> 2777 28.5 9 1864 1864-09-01 00:00:01 blood 1389 #> 2778 28.5 9 1864 1864-09-01 00:00:01 bone 1389 #> 2779 33.9 10 1864 1864-10-01 12:00:00 blood 1390 #> 2780 33.9 10 1864 1864-10-01 12:00:00 bone 1390 #> 2781 57.6 11 1864 1864-11-01 00:00:01 blood 1391 #> 2782 57.6 11 1864 1864-11-01 00:00:01 bone 1391 #> 2783 28.6 12 1864 1864-12-01 12:00:01 blood 1392 #> 2784 28.6 12 1864 1864-12-01 12:00:01 bone 1392 #> 2785 48.7 1 1865 1865-01-01 00:00:00 blood 1393 #> 2786 48.7 1 1865 1865-01-01 00:00:00 bone 1393 #> 2787 39.3 2 1865 1865-01-31 10:00:01 blood 1394 #> 2788 39.3 2 1865 1865-01-31 10:00:01 bone 1394 #> 2789 39.5 3 1865 1865-03-02 20:00:01 blood 1395 #> 2790 39.5 3 1865 1865-03-02 20:00:01 bone 1395 #> 2791 29.4 4 1865 1865-04-02 06:00:00 blood 1396 #> 2792 29.4 4 1865 1865-04-02 06:00:00 bone 1396 #> 2793 34.5 5 1865 1865-05-02 16:00:01 blood 1397 #> 2794 34.5 5 1865 1865-05-02 16:00:01 bone 1397 #> 2795 33.6 6 1865 1865-06-02 02:00:01 blood 1398 #> 2796 33.6 6 1865 1865-06-02 02:00:01 bone 1398 #> 2797 26.8 7 1865 1865-07-02 12:00:00 blood 1399 #> 2798 26.8 7 1865 1865-07-02 12:00:00 bone 1399 #> 2799 37.8 8 1865 1865-08-01 22:00:01 blood 1400 #> 2800 37.8 8 1865 1865-08-01 22:00:01 bone 1400 #> 2801 21.6 9 1865 1865-09-01 08:00:01 blood 1401 #> 2802 21.6 9 1865 1865-09-01 08:00:01 bone 1401 #> 2803 17.1 10 1865 1865-10-01 18:00:00 blood 1402 #> 2804 17.1 10 1865 1865-10-01 18:00:00 bone 1402 #> 2805 24.6 11 1865 1865-11-01 04:00:01 blood 1403 #> 2806 24.6 11 1865 1865-11-01 04:00:01 bone 1403 #> 2807 12.8 12 1865 1865-12-01 14:00:01 blood 1404 #> 2808 12.8 12 1865 1865-12-01 14:00:01 bone 1404 #> 2809 31.6 1 1866 1866-01-01 00:00:00 blood 1405 #> 2810 31.6 1 1866 1866-01-01 00:00:00 bone 1405 #> 2811 38.4 2 1866 1866-01-31 10:00:01 blood 1406 #> 2812 38.4 2 1866 1866-01-31 10:00:01 bone 1406 #> 2813 24.6 3 1866 1866-03-02 20:00:01 blood 1407 #> 2814 24.6 3 1866 1866-03-02 20:00:01 bone 1407 #> 2815 17.6 4 1866 1866-04-02 06:00:00 blood 1408 #> 2816 17.6 4 1866 1866-04-02 06:00:00 bone 1408 #> 2817 12.9 5 1866 1866-05-02 16:00:01 blood 1409 #> 2818 12.9 5 1866 1866-05-02 16:00:01 bone 1409 #> 2819 16.5 6 1866 1866-06-02 02:00:01 blood 1410 #> 2820 16.5 6 1866 1866-06-02 02:00:01 bone 1410 #> 2821 9.3 7 1866 1866-07-02 12:00:00 blood 1411 #> 2822 9.3 7 1866 1866-07-02 12:00:00 bone 1411 #> 2823 12.7 8 1866 1866-08-01 22:00:01 blood 1412 #> 2824 12.7 8 1866 1866-08-01 22:00:01 bone 1412 #> 2825 7.3 9 1866 1866-09-01 08:00:01 blood 1413 #> 2826 7.3 9 1866 1866-09-01 08:00:01 bone 1413 #> 2827 14.1 10 1866 1866-10-01 18:00:00 blood 1414 #> 2828 14.1 10 1866 1866-10-01 18:00:00 bone 1414 #> 2829 9.0 11 1866 1866-11-01 04:00:01 blood 1415 #> 2830 9.0 11 1866 1866-11-01 04:00:01 bone 1415 #> 2831 1.5 12 1866 1866-12-01 14:00:01 blood 1416 #> 2832 1.5 12 1866 1866-12-01 14:00:01 bone 1416 #> 2833 0.0 1 1867 1867-01-01 00:00:00 blood 1417 #> 2834 0.0 1 1867 1867-01-01 00:00:00 bone 1417 #> 2835 0.7 2 1867 1867-01-31 10:00:01 blood 1418 #> 2836 0.7 2 1867 1867-01-31 10:00:01 bone 1418 #> 2837 9.2 3 1867 1867-03-02 20:00:01 blood 1419 #> 2838 9.2 3 1867 1867-03-02 20:00:01 bone 1419 #> 2839 5.1 4 1867 1867-04-02 06:00:00 blood 1420 #> 2840 5.1 4 1867 1867-04-02 06:00:00 bone 1420 #> 2841 2.9 5 1867 1867-05-02 16:00:01 blood 1421 #> 2842 2.9 5 1867 1867-05-02 16:00:01 bone 1421 #> 2843 1.5 6 1867 1867-06-02 02:00:01 blood 1422 #> 2844 1.5 6 1867 1867-06-02 02:00:01 bone 1422 #> 2845 5.0 7 1867 1867-07-02 12:00:00 blood 1423 #> 2846 5.0 7 1867 1867-07-02 12:00:00 bone 1423 #> 2847 4.9 8 1867 1867-08-01 22:00:01 blood 1424 #> 2848 4.9 8 1867 1867-08-01 22:00:01 bone 1424 #> 2849 9.8 9 1867 1867-09-01 08:00:01 blood 1425 #> 2850 9.8 9 1867 1867-09-01 08:00:01 bone 1425 #> 2851 13.5 10 1867 1867-10-01 18:00:00 blood 1426 #> 2852 13.5 10 1867 1867-10-01 18:00:00 bone 1426 #> 2853 9.3 11 1867 1867-11-01 04:00:01 blood 1427 #> 2854 9.3 11 1867 1867-11-01 04:00:01 bone 1427 #> 2855 25.2 12 1867 1867-12-01 14:00:01 blood 1428 #> 2856 25.2 12 1867 1867-12-01 14:00:01 bone 1428 #> 2857 15.6 1 1868 1868-01-01 00:00:00 blood 1429 #> 2858 15.6 1 1868 1868-01-01 00:00:00 bone 1429 #> 2859 15.8 2 1868 1868-01-31 12:00:01 blood 1430 #> 2860 15.8 2 1868 1868-01-31 12:00:01 bone 1430 #> 2861 26.5 3 1868 1868-03-02 00:00:01 blood 1431 #> 2862 26.5 3 1868 1868-03-02 00:00:01 bone 1431 #> 2863 36.6 4 1868 1868-04-01 12:00:00 blood 1432 #> 2864 36.6 4 1868 1868-04-01 12:00:00 bone 1432 #> 2865 26.7 5 1868 1868-05-02 00:00:01 blood 1433 #> 2866 26.7 5 1868 1868-05-02 00:00:01 bone 1433 #> 2867 31.1 6 1868 1868-06-01 12:00:01 blood 1434 #> 2868 31.1 6 1868 1868-06-01 12:00:01 bone 1434 #> 2869 28.6 7 1868 1868-07-02 00:00:00 blood 1435 #> 2870 28.6 7 1868 1868-07-02 00:00:00 bone 1435 #> 2871 34.4 8 1868 1868-08-01 12:00:01 blood 1436 #> 2872 34.4 8 1868 1868-08-01 12:00:01 bone 1436 #> 2873 43.8 9 1868 1868-09-01 00:00:01 blood 1437 #> 2874 43.8 9 1868 1868-09-01 00:00:01 bone 1437 #> 2875 61.7 10 1868 1868-10-01 12:00:00 blood 1438 #> 2876 61.7 10 1868 1868-10-01 12:00:00 bone 1438 #> 2877 59.1 11 1868 1868-11-01 00:00:01 blood 1439 #> 2878 59.1 11 1868 1868-11-01 00:00:01 bone 1439 #> 2879 67.6 12 1868 1868-12-01 12:00:01 blood 1440 #> 2880 67.6 12 1868 1868-12-01 12:00:01 bone 1440 #> 2881 60.9 1 1869 1869-01-01 00:00:00 blood 1441 #> 2882 60.9 1 1869 1869-01-01 00:00:00 bone 1441 #> 2883 59.3 2 1869 1869-01-31 10:00:01 blood 1442 #> 2884 59.3 2 1869 1869-01-31 10:00:01 bone 1442 #> 2885 52.7 3 1869 1869-03-02 20:00:01 blood 1443 #> 2886 52.7 3 1869 1869-03-02 20:00:01 bone 1443 #> 2887 41.0 4 1869 1869-04-02 06:00:00 blood 1444 #> 2888 41.0 4 1869 1869-04-02 06:00:00 bone 1444 #> 2889 104.0 5 1869 1869-05-02 16:00:01 blood 1445 #> 2890 104.0 5 1869 1869-05-02 16:00:01 bone 1445 #> 2891 108.4 6 1869 1869-06-02 02:00:01 blood 1446 #> 2892 108.4 6 1869 1869-06-02 02:00:01 bone 1446 #> 2893 59.2 7 1869 1869-07-02 12:00:00 blood 1447 #> 2894 59.2 7 1869 1869-07-02 12:00:00 bone 1447 #> 2895 79.6 8 1869 1869-08-01 22:00:01 blood 1448 #> 2896 79.6 8 1869 1869-08-01 22:00:01 bone 1448 #> 2897 80.6 9 1869 1869-09-01 08:00:01 blood 1449 #> 2898 80.6 9 1869 1869-09-01 08:00:01 bone 1449 #> 2899 59.4 10 1869 1869-10-01 18:00:00 blood 1450 #> 2900 59.4 10 1869 1869-10-01 18:00:00 bone 1450 #> 2901 77.4 11 1869 1869-11-01 04:00:01 blood 1451 #> 2902 77.4 11 1869 1869-11-01 04:00:01 bone 1451 #> 2903 104.3 12 1869 1869-12-01 14:00:01 blood 1452 #> 2904 104.3 12 1869 1869-12-01 14:00:01 bone 1452 #> 2905 77.3 1 1870 1870-01-01 00:00:00 blood 1453 #> 2906 77.3 1 1870 1870-01-01 00:00:00 bone 1453 #> 2907 114.9 2 1870 1870-01-31 10:00:01 blood 1454 #> 2908 114.9 2 1870 1870-01-31 10:00:01 bone 1454 #> 2909 159.4 3 1870 1870-03-02 20:00:01 blood 1455 #> 2910 159.4 3 1870 1870-03-02 20:00:01 bone 1455 #> 2911 160.0 4 1870 1870-04-02 06:00:00 blood 1456 #> 2912 160.0 4 1870 1870-04-02 06:00:00 bone 1456 #> 2913 176.0 5 1870 1870-05-02 16:00:01 blood 1457 #> 2914 176.0 5 1870 1870-05-02 16:00:01 bone 1457 #> 2915 135.6 6 1870 1870-06-02 02:00:01 blood 1458 #> 2916 135.6 6 1870 1870-06-02 02:00:01 bone 1458 #> 2917 132.4 7 1870 1870-07-02 12:00:00 blood 1459 #> 2918 132.4 7 1870 1870-07-02 12:00:00 bone 1459 #> 2919 153.8 8 1870 1870-08-01 22:00:01 blood 1460 #> 2920 153.8 8 1870 1870-08-01 22:00:01 bone 1460 #> 2921 136.0 9 1870 1870-09-01 08:00:01 blood 1461 #> 2922 136.0 9 1870 1870-09-01 08:00:01 bone 1461 #> 2923 146.4 10 1870 1870-10-01 18:00:00 blood 1462 #> 2924 146.4 10 1870 1870-10-01 18:00:00 bone 1462 #> 2925 147.5 11 1870 1870-11-01 04:00:01 blood 1463 #> 2926 147.5 11 1870 1870-11-01 04:00:01 bone 1463 #> 2927 130.0 12 1870 1870-12-01 14:00:01 blood 1464 #> 2928 130.0 12 1870 1870-12-01 14:00:01 bone 1464 #> 2929 88.3 1 1871 1871-01-01 00:00:00 blood 1465 #> 2930 88.3 1 1871 1871-01-01 00:00:00 bone 1465 #> 2931 125.3 2 1871 1871-01-31 10:00:01 blood 1466 #> 2932 125.3 2 1871 1871-01-31 10:00:01 bone 1466 #> 2933 143.2 3 1871 1871-03-02 20:00:01 blood 1467 #> 2934 143.2 3 1871 1871-03-02 20:00:01 bone 1467 #> 2935 162.4 4 1871 1871-04-02 06:00:00 blood 1468 #> 2936 162.4 4 1871 1871-04-02 06:00:00 bone 1468 #> 2937 145.5 5 1871 1871-05-02 16:00:01 blood 1469 #> 2938 145.5 5 1871 1871-05-02 16:00:01 bone 1469 #> 2939 91.7 6 1871 1871-06-02 02:00:01 blood 1470 #> 2940 91.7 6 1871 1871-06-02 02:00:01 bone 1470 #> 2941 103.0 7 1871 1871-07-02 12:00:00 blood 1471 #> 2942 103.0 7 1871 1871-07-02 12:00:00 bone 1471 #> 2943 110.0 8 1871 1871-08-01 22:00:01 blood 1472 #> 2944 110.0 8 1871 1871-08-01 22:00:01 bone 1472 #> 2945 80.3 9 1871 1871-09-01 08:00:01 blood 1473 #> 2946 80.3 9 1871 1871-09-01 08:00:01 bone 1473 #> 2947 89.0 10 1871 1871-10-01 18:00:00 blood 1474 #> 2948 89.0 10 1871 1871-10-01 18:00:00 bone 1474 #> 2949 105.4 11 1871 1871-11-01 04:00:01 blood 1475 #> 2950 105.4 11 1871 1871-11-01 04:00:01 bone 1475 #> 2951 90.3 12 1871 1871-12-01 14:00:01 blood 1476 #> 2952 90.3 12 1871 1871-12-01 14:00:01 bone 1476 #> 2953 79.5 1 1872 1872-01-01 00:00:00 blood 1477 #> 2954 79.5 1 1872 1872-01-01 00:00:00 bone 1477 #> 2955 120.1 2 1872 1872-01-31 12:00:01 blood 1478 #> 2956 120.1 2 1872 1872-01-31 12:00:01 bone 1478 #> 2957 88.4 3 1872 1872-03-02 00:00:01 blood 1479 #> 2958 88.4 3 1872 1872-03-02 00:00:01 bone 1479 #> 2959 102.1 4 1872 1872-04-01 12:00:00 blood 1480 #> 2960 102.1 4 1872 1872-04-01 12:00:00 bone 1480 #> 2961 107.6 5 1872 1872-05-02 00:00:01 blood 1481 #> 2962 107.6 5 1872 1872-05-02 00:00:01 bone 1481 #> 2963 109.9 6 1872 1872-06-01 12:00:01 blood 1482 #> 2964 109.9 6 1872 1872-06-01 12:00:01 bone 1482 #> 2965 105.5 7 1872 1872-07-02 00:00:00 blood 1483 #> 2966 105.5 7 1872 1872-07-02 00:00:00 bone 1483 #> 2967 92.9 8 1872 1872-08-01 12:00:01 blood 1484 #> 2968 92.9 8 1872 1872-08-01 12:00:01 bone 1484 #> 2969 114.6 9 1872 1872-09-01 00:00:01 blood 1485 #> 2970 114.6 9 1872 1872-09-01 00:00:01 bone 1485 #> 2971 103.5 10 1872 1872-10-01 12:00:00 blood 1486 #> 2972 103.5 10 1872 1872-10-01 12:00:00 bone 1486 #> 2973 112.0 11 1872 1872-11-01 00:00:01 blood 1487 #> 2974 112.0 11 1872 1872-11-01 00:00:01 bone 1487 #> 2975 83.9 12 1872 1872-12-01 12:00:01 blood 1488 #> 2976 83.9 12 1872 1872-12-01 12:00:01 bone 1488 #> 2977 86.7 1 1873 1873-01-01 00:00:00 blood 1489 #> 2978 86.7 1 1873 1873-01-01 00:00:00 bone 1489 #> 2979 107.0 2 1873 1873-01-31 10:00:01 blood 1490 #> 2980 107.0 2 1873 1873-01-31 10:00:01 bone 1490 #> 2981 98.3 3 1873 1873-03-02 20:00:01 blood 1491 #> 2982 98.3 3 1873 1873-03-02 20:00:01 bone 1491 #> 2983 76.2 4 1873 1873-04-02 06:00:00 blood 1492 #> 2984 76.2 4 1873 1873-04-02 06:00:00 bone 1492 #> 2985 47.9 5 1873 1873-05-02 16:00:01 blood 1493 #> 2986 47.9 5 1873 1873-05-02 16:00:01 bone 1493 #> 2987 44.8 6 1873 1873-06-02 02:00:01 blood 1494 #> 2988 44.8 6 1873 1873-06-02 02:00:01 bone 1494 #> 2989 66.9 7 1873 1873-07-02 12:00:00 blood 1495 #> 2990 66.9 7 1873 1873-07-02 12:00:00 bone 1495 #> 2991 68.2 8 1873 1873-08-01 22:00:01 blood 1496 #> 2992 68.2 8 1873 1873-08-01 22:00:01 bone 1496 #> 2993 47.5 9 1873 1873-09-01 08:00:01 blood 1497 #> 2994 47.5 9 1873 1873-09-01 08:00:01 bone 1497 #> 2995 47.4 10 1873 1873-10-01 18:00:00 blood 1498 #> 2996 47.4 10 1873 1873-10-01 18:00:00 bone 1498 #> 2997 55.4 11 1873 1873-11-01 04:00:01 blood 1499 #> 2998 55.4 11 1873 1873-11-01 04:00:01 bone 1499 #> 2999 49.2 12 1873 1873-12-01 14:00:01 blood 1500 #> 3000 49.2 12 1873 1873-12-01 14:00:01 bone 1500 #> 3001 60.8 1 1874 1874-01-01 00:00:00 blood 1501 #> 3002 60.8 1 1874 1874-01-01 00:00:00 bone 1501 #> 3003 64.2 2 1874 1874-01-31 10:00:01 blood 1502 #> 3004 64.2 2 1874 1874-01-31 10:00:01 bone 1502 #> 3005 46.4 3 1874 1874-03-02 20:00:01 blood 1503 #> 3006 46.4 3 1874 1874-03-02 20:00:01 bone 1503 #> 3007 32.0 4 1874 1874-04-02 06:00:00 blood 1504 #> 3008 32.0 4 1874 1874-04-02 06:00:00 bone 1504 #> 3009 44.6 5 1874 1874-05-02 16:00:01 blood 1505 #> 3010 44.6 5 1874 1874-05-02 16:00:01 bone 1505 #> 3011 38.2 6 1874 1874-06-02 02:00:01 blood 1506 #> 3012 38.2 6 1874 1874-06-02 02:00:01 bone 1506 #> 3013 67.8 7 1874 1874-07-02 12:00:00 blood 1507 #> 3014 67.8 7 1874 1874-07-02 12:00:00 bone 1507 #> 3015 61.3 8 1874 1874-08-01 22:00:01 blood 1508 #> 3016 61.3 8 1874 1874-08-01 22:00:01 bone 1508 #> 3017 28.0 9 1874 1874-09-01 08:00:01 blood 1509 #> 3018 28.0 9 1874 1874-09-01 08:00:01 bone 1509 #> 3019 34.3 10 1874 1874-10-01 18:00:00 blood 1510 #> 3020 34.3 10 1874 1874-10-01 18:00:00 bone 1510 #> 3021 28.9 11 1874 1874-11-01 04:00:01 blood 1511 #> 3022 28.9 11 1874 1874-11-01 04:00:01 bone 1511 #> 3023 29.3 12 1874 1874-12-01 14:00:01 blood 1512 #> 3024 29.3 12 1874 1874-12-01 14:00:01 bone 1512 #> 3025 14.6 1 1875 1875-01-01 00:00:00 blood 1513 #> 3026 14.6 1 1875 1875-01-01 00:00:00 bone 1513 #> 3027 22.2 2 1875 1875-01-31 10:00:01 blood 1514 #> 3028 22.2 2 1875 1875-01-31 10:00:01 bone 1514 #> 3029 33.8 3 1875 1875-03-02 20:00:01 blood 1515 #> 3030 33.8 3 1875 1875-03-02 20:00:01 bone 1515 #> 3031 29.1 4 1875 1875-04-02 06:00:00 blood 1516 #> 3032 29.1 4 1875 1875-04-02 06:00:00 bone 1516 #> 3033 11.5 5 1875 1875-05-02 16:00:01 blood 1517 #> 3034 11.5 5 1875 1875-05-02 16:00:01 bone 1517 #> 3035 23.9 6 1875 1875-06-02 02:00:01 blood 1518 #> 3036 23.9 6 1875 1875-06-02 02:00:01 bone 1518 #> 3037 12.5 7 1875 1875-07-02 12:00:00 blood 1519 #> 3038 12.5 7 1875 1875-07-02 12:00:00 bone 1519 #> 3039 14.6 8 1875 1875-08-01 22:00:01 blood 1520 #> 3040 14.6 8 1875 1875-08-01 22:00:01 bone 1520 #> 3041 2.4 9 1875 1875-09-01 08:00:01 blood 1521 #> 3042 2.4 9 1875 1875-09-01 08:00:01 bone 1521 #> 3043 12.7 10 1875 1875-10-01 18:00:00 blood 1522 #> 3044 12.7 10 1875 1875-10-01 18:00:00 bone 1522 #> 3045 17.7 11 1875 1875-11-01 04:00:01 blood 1523 #> 3046 17.7 11 1875 1875-11-01 04:00:01 bone 1523 #> 3047 9.9 12 1875 1875-12-01 14:00:01 blood 1524 #> 3048 9.9 12 1875 1875-12-01 14:00:01 bone 1524 #> 3049 14.3 1 1876 1876-01-01 00:00:00 blood 1525 #> 3050 14.3 1 1876 1876-01-01 00:00:00 bone 1525 #> 3051 15.0 2 1876 1876-01-31 12:00:01 blood 1526 #> 3052 15.0 2 1876 1876-01-31 12:00:01 bone 1526 #> 3053 31.2 3 1876 1876-03-02 00:00:01 blood 1527 #> 3054 31.2 3 1876 1876-03-02 00:00:01 bone 1527 #> 3055 2.3 4 1876 1876-04-01 12:00:00 blood 1528 #> 3056 2.3 4 1876 1876-04-01 12:00:00 bone 1528 #> 3057 5.1 5 1876 1876-05-02 00:00:01 blood 1529 #> 3058 5.1 5 1876 1876-05-02 00:00:01 bone 1529 #> 3059 1.6 6 1876 1876-06-01 12:00:01 blood 1530 #> 3060 1.6 6 1876 1876-06-01 12:00:01 bone 1530 #> 3061 15.2 7 1876 1876-07-02 00:00:00 blood 1531 #> 3062 15.2 7 1876 1876-07-02 00:00:00 bone 1531 #> 3063 8.8 8 1876 1876-08-01 12:00:01 blood 1532 #> 3064 8.8 8 1876 1876-08-01 12:00:01 bone 1532 #> 3065 9.9 9 1876 1876-09-01 00:00:01 blood 1533 #> 3066 9.9 9 1876 1876-09-01 00:00:01 bone 1533 #> 3067 14.3 10 1876 1876-10-01 12:00:00 blood 1534 #> 3068 14.3 10 1876 1876-10-01 12:00:00 bone 1534 #> 3069 9.9 11 1876 1876-11-01 00:00:01 blood 1535 #> 3070 9.9 11 1876 1876-11-01 00:00:01 bone 1535 #> 3071 8.2 12 1876 1876-12-01 12:00:01 blood 1536 #> 3072 8.2 12 1876 1876-12-01 12:00:01 bone 1536 #> 3073 24.4 1 1877 1877-01-01 00:00:00 blood 1537 #> 3074 24.4 1 1877 1877-01-01 00:00:00 bone 1537 #> 3075 8.7 2 1877 1877-01-31 10:00:01 blood 1538 #> 3076 8.7 2 1877 1877-01-31 10:00:01 bone 1538 #> 3077 11.7 3 1877 1877-03-02 20:00:01 blood 1539 #> 3078 11.7 3 1877 1877-03-02 20:00:01 bone 1539 #> 3079 15.8 4 1877 1877-04-02 06:00:00 blood 1540 #> 3080 15.8 4 1877 1877-04-02 06:00:00 bone 1540 #> 3081 21.2 5 1877 1877-05-02 16:00:01 blood 1541 #> 3082 21.2 5 1877 1877-05-02 16:00:01 bone 1541 #> 3083 13.4 6 1877 1877-06-02 02:00:01 blood 1542 #> 3084 13.4 6 1877 1877-06-02 02:00:01 bone 1542 #> 3085 5.9 7 1877 1877-07-02 12:00:00 blood 1543 #> 3086 5.9 7 1877 1877-07-02 12:00:00 bone 1543 #> 3087 6.3 8 1877 1877-08-01 22:00:01 blood 1544 #> 3088 6.3 8 1877 1877-08-01 22:00:01 bone 1544 #> 3089 16.4 9 1877 1877-09-01 08:00:01 blood 1545 #> 3090 16.4 9 1877 1877-09-01 08:00:01 bone 1545 #> 3091 6.7 10 1877 1877-10-01 18:00:00 blood 1546 #> 3092 6.7 10 1877 1877-10-01 18:00:00 bone 1546 #> 3093 14.5 11 1877 1877-11-01 04:00:01 blood 1547 #> 3094 14.5 11 1877 1877-11-01 04:00:01 bone 1547 #> 3095 2.3 12 1877 1877-12-01 14:00:01 blood 1548 #> 3096 2.3 12 1877 1877-12-01 14:00:01 bone 1548 #> 3097 3.3 1 1878 1878-01-01 00:00:00 blood 1549 #> 3098 3.3 1 1878 1878-01-01 00:00:00 bone 1549 #> 3099 6.0 2 1878 1878-01-31 10:00:01 blood 1550 #> 3100 6.0 2 1878 1878-01-31 10:00:01 bone 1550 #> 3101 7.8 3 1878 1878-03-02 20:00:01 blood 1551 #> 3102 7.8 3 1878 1878-03-02 20:00:01 bone 1551 #> 3103 0.1 4 1878 1878-04-02 06:00:00 blood 1552 #> 3104 0.1 4 1878 1878-04-02 06:00:00 bone 1552 #> 3105 5.8 5 1878 1878-05-02 16:00:01 blood 1553 #> 3106 5.8 5 1878 1878-05-02 16:00:01 bone 1553 #> 3107 6.4 6 1878 1878-06-02 02:00:01 blood 1554 #> 3108 6.4 6 1878 1878-06-02 02:00:01 bone 1554 #> 3109 0.1 7 1878 1878-07-02 12:00:00 blood 1555 #> 3110 0.1 7 1878 1878-07-02 12:00:00 bone 1555 #> 3111 0.0 8 1878 1878-08-01 22:00:01 blood 1556 #> 3112 0.0 8 1878 1878-08-01 22:00:01 bone 1556 #> 3113 5.3 9 1878 1878-09-01 08:00:01 blood 1557 #> 3114 5.3 9 1878 1878-09-01 08:00:01 bone 1557 #> 3115 1.1 10 1878 1878-10-01 18:00:00 blood 1558 #> 3116 1.1 10 1878 1878-10-01 18:00:00 bone 1558 #> 3117 4.1 11 1878 1878-11-01 04:00:01 blood 1559 #> 3118 4.1 11 1878 1878-11-01 04:00:01 bone 1559 #> 3119 0.5 12 1878 1878-12-01 14:00:01 blood 1560 #> 3120 0.5 12 1878 1878-12-01 14:00:01 bone 1560 #> 3121 0.8 1 1879 1879-01-01 00:00:00 blood 1561 #> 3122 0.8 1 1879 1879-01-01 00:00:00 bone 1561 #> 3123 0.6 2 1879 1879-01-31 10:00:01 blood 1562 #> 3124 0.6 2 1879 1879-01-31 10:00:01 bone 1562 #> 3125 0.0 3 1879 1879-03-02 20:00:01 blood 1563 #> 3126 0.0 3 1879 1879-03-02 20:00:01 bone 1563 #> 3127 6.2 4 1879 1879-04-02 06:00:00 blood 1564 #> 3128 6.2 4 1879 1879-04-02 06:00:00 bone 1564 #> 3129 2.4 5 1879 1879-05-02 16:00:01 blood 1565 #> 3130 2.4 5 1879 1879-05-02 16:00:01 bone 1565 #> 3131 4.8 6 1879 1879-06-02 02:00:01 blood 1566 #> 3132 4.8 6 1879 1879-06-02 02:00:01 bone 1566 #> 3133 7.5 7 1879 1879-07-02 12:00:00 blood 1567 #> 3134 7.5 7 1879 1879-07-02 12:00:00 bone 1567 #> 3135 10.7 8 1879 1879-08-01 22:00:01 blood 1568 #> 3136 10.7 8 1879 1879-08-01 22:00:01 bone 1568 #> 3137 6.1 9 1879 1879-09-01 08:00:01 blood 1569 #> 3138 6.1 9 1879 1879-09-01 08:00:01 bone 1569 #> 3139 12.3 10 1879 1879-10-01 18:00:00 blood 1570 #> 3140 12.3 10 1879 1879-10-01 18:00:00 bone 1570 #> 3141 12.9 11 1879 1879-11-01 04:00:01 blood 1571 #> 3142 12.9 11 1879 1879-11-01 04:00:01 bone 1571 #> 3143 7.2 12 1879 1879-12-01 14:00:01 blood 1572 #> 3144 7.2 12 1879 1879-12-01 14:00:01 bone 1572 #> 3145 24.0 1 1880 1880-01-01 00:00:00 blood 1573 #> 3146 24.0 1 1880 1880-01-01 00:00:00 bone 1573 #> 3147 27.5 2 1880 1880-01-31 12:00:01 blood 1574 #> 3148 27.5 2 1880 1880-01-31 12:00:01 bone 1574 #> 3149 19.5 3 1880 1880-03-02 00:00:01 blood 1575 #> 3150 19.5 3 1880 1880-03-02 00:00:01 bone 1575 #> 3151 19.3 4 1880 1880-04-01 12:00:00 blood 1576 #> 3152 19.3 4 1880 1880-04-01 12:00:00 bone 1576 #> 3153 23.5 5 1880 1880-05-02 00:00:01 blood 1577 #> 3154 23.5 5 1880 1880-05-02 00:00:01 bone 1577 #> 3155 34.1 6 1880 1880-06-01 12:00:01 blood 1578 #> 3156 34.1 6 1880 1880-06-01 12:00:01 bone 1578 #> 3157 21.9 7 1880 1880-07-02 00:00:00 blood 1579 #> 3158 21.9 7 1880 1880-07-02 00:00:00 bone 1579 #> 3159 48.1 8 1880 1880-08-01 12:00:01 blood 1580 #> 3160 48.1 8 1880 1880-08-01 12:00:01 bone 1580 #> 3161 66.0 9 1880 1880-09-01 00:00:01 blood 1581 #> 3162 66.0 9 1880 1880-09-01 00:00:01 bone 1581 #> 3163 43.0 10 1880 1880-10-01 12:00:00 blood 1582 #> 3164 43.0 10 1880 1880-10-01 12:00:00 bone 1582 #> 3165 30.7 11 1880 1880-11-01 00:00:01 blood 1583 #> 3166 30.7 11 1880 1880-11-01 00:00:01 bone 1583 #> 3167 29.6 12 1880 1880-12-01 12:00:01 blood 1584 #> 3168 29.6 12 1880 1880-12-01 12:00:01 bone 1584 #> 3169 36.4 1 1881 1881-01-01 00:00:00 blood 1585 #> 3170 36.4 1 1881 1881-01-01 00:00:00 bone 1585 #> 3171 53.2 2 1881 1881-01-31 10:00:01 blood 1586 #> 3172 53.2 2 1881 1881-01-31 10:00:01 bone 1586 #> 3173 51.5 3 1881 1881-03-02 20:00:01 blood 1587 #> 3174 51.5 3 1881 1881-03-02 20:00:01 bone 1587 #> 3175 51.7 4 1881 1881-04-02 06:00:00 blood 1588 #> 3176 51.7 4 1881 1881-04-02 06:00:00 bone 1588 #> 3177 43.5 5 1881 1881-05-02 16:00:01 blood 1589 #> 3178 43.5 5 1881 1881-05-02 16:00:01 bone 1589 #> 3179 60.5 6 1881 1881-06-02 02:00:01 blood 1590 #> 3180 60.5 6 1881 1881-06-02 02:00:01 bone 1590 #> 3181 76.9 7 1881 1881-07-02 12:00:00 blood 1591 #> 3182 76.9 7 1881 1881-07-02 12:00:00 bone 1591 #> 3183 58.0 8 1881 1881-08-01 22:00:01 blood 1592 #> 3184 58.0 8 1881 1881-08-01 22:00:01 bone 1592 #> 3185 53.2 9 1881 1881-09-01 08:00:01 blood 1593 #> 3186 53.2 9 1881 1881-09-01 08:00:01 bone 1593 #> 3187 64.0 10 1881 1881-10-01 18:00:00 blood 1594 #> 3188 64.0 10 1881 1881-10-01 18:00:00 bone 1594 #> 3189 54.8 11 1881 1881-11-01 04:00:01 blood 1595 #> 3190 54.8 11 1881 1881-11-01 04:00:01 bone 1595 #> 3191 47.3 12 1881 1881-12-01 14:00:01 blood 1596 #> 3192 47.3 12 1881 1881-12-01 14:00:01 bone 1596 #> 3193 45.0 1 1882 1882-01-01 00:00:00 blood 1597 #> 3194 45.0 1 1882 1882-01-01 00:00:00 bone 1597 #> 3195 69.3 2 1882 1882-01-31 10:00:01 blood 1598 #> 3196 69.3 2 1882 1882-01-31 10:00:01 bone 1598 #> 3197 67.5 3 1882 1882-03-02 20:00:01 blood 1599 #> 3198 67.5 3 1882 1882-03-02 20:00:01 bone 1599 #> 3199 95.8 4 1882 1882-04-02 06:00:00 blood 1600 #> 3200 95.8 4 1882 1882-04-02 06:00:00 bone 1600 #> 3201 64.1 5 1882 1882-05-02 16:00:01 blood 1601 #> 3202 64.1 5 1882 1882-05-02 16:00:01 bone 1601 #> 3203 45.2 6 1882 1882-06-02 02:00:01 blood 1602 #> 3204 45.2 6 1882 1882-06-02 02:00:01 bone 1602 #> 3205 45.4 7 1882 1882-07-02 12:00:00 blood 1603 #> 3206 45.4 7 1882 1882-07-02 12:00:00 bone 1603 #> 3207 40.4 8 1882 1882-08-01 22:00:01 blood 1604 #> 3208 40.4 8 1882 1882-08-01 22:00:01 bone 1604 #> 3209 57.7 9 1882 1882-09-01 08:00:01 blood 1605 #> 3210 57.7 9 1882 1882-09-01 08:00:01 bone 1605 #> 3211 59.2 10 1882 1882-10-01 18:00:00 blood 1606 #> 3212 59.2 10 1882 1882-10-01 18:00:00 bone 1606 #> 3213 84.4 11 1882 1882-11-01 04:00:01 blood 1607 #> 3214 84.4 11 1882 1882-11-01 04:00:01 bone 1607 #> 3215 41.8 12 1882 1882-12-01 14:00:01 blood 1608 #> 3216 41.8 12 1882 1882-12-01 14:00:01 bone 1608 #> 3217 60.6 1 1883 1883-01-01 00:00:00 blood 1609 #> 3218 60.6 1 1883 1883-01-01 00:00:00 bone 1609 #> 3219 46.9 2 1883 1883-01-31 10:00:01 blood 1610 #> 3220 46.9 2 1883 1883-01-31 10:00:01 bone 1610 #> 3221 42.8 3 1883 1883-03-02 20:00:01 blood 1611 #> 3222 42.8 3 1883 1883-03-02 20:00:01 bone 1611 #> 3223 82.1 4 1883 1883-04-02 06:00:00 blood 1612 #> 3224 82.1 4 1883 1883-04-02 06:00:00 bone 1612 #> 3225 32.1 5 1883 1883-05-02 16:00:01 blood 1613 #> 3226 32.1 5 1883 1883-05-02 16:00:01 bone 1613 #> 3227 76.5 6 1883 1883-06-02 02:00:01 blood 1614 #> 3228 76.5 6 1883 1883-06-02 02:00:01 bone 1614 #> 3229 80.6 7 1883 1883-07-02 12:00:00 blood 1615 #> 3230 80.6 7 1883 1883-07-02 12:00:00 bone 1615 #> 3231 46.0 8 1883 1883-08-01 22:00:01 blood 1616 #> 3232 46.0 8 1883 1883-08-01 22:00:01 bone 1616 #> 3233 52.6 9 1883 1883-09-01 08:00:01 blood 1617 #> 3234 52.6 9 1883 1883-09-01 08:00:01 bone 1617 #> 3235 83.8 10 1883 1883-10-01 18:00:00 blood 1618 #> 3236 83.8 10 1883 1883-10-01 18:00:00 bone 1618 #> 3237 84.5 11 1883 1883-11-01 04:00:01 blood 1619 #> 3238 84.5 11 1883 1883-11-01 04:00:01 bone 1619 #> 3239 75.9 12 1883 1883-12-01 14:00:01 blood 1620 #> 3240 75.9 12 1883 1883-12-01 14:00:01 bone 1620 #> 3241 91.5 1 1884 1884-01-01 00:00:00 blood 1621 #> 3242 91.5 1 1884 1884-01-01 00:00:00 bone 1621 #> 3243 86.9 2 1884 1884-01-31 12:00:01 blood 1622 #> 3244 86.9 2 1884 1884-01-31 12:00:01 bone 1622 #> 3245 86.8 3 1884 1884-03-02 00:00:01 blood 1623 #> 3246 86.8 3 1884 1884-03-02 00:00:01 bone 1623 #> 3247 76.1 4 1884 1884-04-01 12:00:00 blood 1624 #> 3248 76.1 4 1884 1884-04-01 12:00:00 bone 1624 #> 3249 66.5 5 1884 1884-05-02 00:00:01 blood 1625 #> 3250 66.5 5 1884 1884-05-02 00:00:01 bone 1625 #> 3251 51.2 6 1884 1884-06-01 12:00:01 blood 1626 #> 3252 51.2 6 1884 1884-06-01 12:00:01 bone 1626 #> 3253 53.1 7 1884 1884-07-02 00:00:00 blood 1627 #> 3254 53.1 7 1884 1884-07-02 00:00:00 bone 1627 #> 3255 55.8 8 1884 1884-08-01 12:00:01 blood 1628 #> 3256 55.8 8 1884 1884-08-01 12:00:01 bone 1628 #> 3257 61.9 9 1884 1884-09-01 00:00:01 blood 1629 #> 3258 61.9 9 1884 1884-09-01 00:00:01 bone 1629 #> 3259 47.8 10 1884 1884-10-01 12:00:00 blood 1630 #> 3260 47.8 10 1884 1884-10-01 12:00:00 bone 1630 #> 3261 36.6 11 1884 1884-11-01 00:00:01 blood 1631 #> 3262 36.6 11 1884 1884-11-01 00:00:01 bone 1631 #> 3263 47.2 12 1884 1884-12-01 12:00:01 blood 1632 #> 3264 47.2 12 1884 1884-12-01 12:00:01 bone 1632 #> 3265 42.8 1 1885 1885-01-01 00:00:00 blood 1633 #> 3266 42.8 1 1885 1885-01-01 00:00:00 bone 1633 #> 3267 71.8 2 1885 1885-01-31 10:00:01 blood 1634 #> 3268 71.8 2 1885 1885-01-31 10:00:01 bone 1634 #> 3269 49.8 3 1885 1885-03-02 20:00:01 blood 1635 #> 3270 49.8 3 1885 1885-03-02 20:00:01 bone 1635 #> 3271 55.0 4 1885 1885-04-02 06:00:00 blood 1636 #> 3272 55.0 4 1885 1885-04-02 06:00:00 bone 1636 #> 3273 73.0 5 1885 1885-05-02 16:00:01 blood 1637 #> 3274 73.0 5 1885 1885-05-02 16:00:01 bone 1637 #> 3275 83.7 6 1885 1885-06-02 02:00:01 blood 1638 #> 3276 83.7 6 1885 1885-06-02 02:00:01 bone 1638 #> 3277 66.5 7 1885 1885-07-02 12:00:00 blood 1639 #> 3278 66.5 7 1885 1885-07-02 12:00:00 bone 1639 #> 3279 50.0 8 1885 1885-08-01 22:00:01 blood 1640 #> 3280 50.0 8 1885 1885-08-01 22:00:01 bone 1640 #> 3281 39.6 9 1885 1885-09-01 08:00:01 blood 1641 #> 3282 39.6 9 1885 1885-09-01 08:00:01 bone 1641 #> 3283 38.7 10 1885 1885-10-01 18:00:00 blood 1642 #> 3284 38.7 10 1885 1885-10-01 18:00:00 bone 1642 #> 3285 33.3 11 1885 1885-11-01 04:00:01 blood 1643 #> 3286 33.3 11 1885 1885-11-01 04:00:01 bone 1643 #> 3287 21.7 12 1885 1885-12-01 14:00:01 blood 1644 #> 3288 21.7 12 1885 1885-12-01 14:00:01 bone 1644 #> 3289 29.9 1 1886 1886-01-01 00:00:00 blood 1645 #> 3290 29.9 1 1886 1886-01-01 00:00:00 bone 1645 #> 3291 25.9 2 1886 1886-01-31 10:00:01 blood 1646 #> 3292 25.9 2 1886 1886-01-31 10:00:01 bone 1646 #> 3293 57.3 3 1886 1886-03-02 20:00:01 blood 1647 #> 3294 57.3 3 1886 1886-03-02 20:00:01 bone 1647 #> 3295 43.7 4 1886 1886-04-02 06:00:00 blood 1648 #> 3296 43.7 4 1886 1886-04-02 06:00:00 bone 1648 #> 3297 30.7 5 1886 1886-05-02 16:00:01 blood 1649 #> 3298 30.7 5 1886 1886-05-02 16:00:01 bone 1649 #> 3299 27.1 6 1886 1886-06-02 02:00:01 blood 1650 #> 3300 27.1 6 1886 1886-06-02 02:00:01 bone 1650 #> 3301 30.3 7 1886 1886-07-02 12:00:00 blood 1651 #> 3302 30.3 7 1886 1886-07-02 12:00:00 bone 1651 #> 3303 16.9 8 1886 1886-08-01 22:00:01 blood 1652 #> 3304 16.9 8 1886 1886-08-01 22:00:01 bone 1652 #> 3305 21.4 9 1886 1886-09-01 08:00:01 blood 1653 #> 3306 21.4 9 1886 1886-09-01 08:00:01 bone 1653 #> 3307 8.6 10 1886 1886-10-01 18:00:00 blood 1654 #> 3308 8.6 10 1886 1886-10-01 18:00:00 bone 1654 #> 3309 0.3 11 1886 1886-11-01 04:00:01 blood 1655 #> 3310 0.3 11 1886 1886-11-01 04:00:01 bone 1655 #> 3311 12.4 12 1886 1886-12-01 14:00:01 blood 1656 #> 3312 12.4 12 1886 1886-12-01 14:00:01 bone 1656 #> 3313 10.3 1 1887 1887-01-01 00:00:00 blood 1657 #> 3314 10.3 1 1887 1887-01-01 00:00:00 bone 1657 #> 3315 13.2 2 1887 1887-01-31 10:00:01 blood 1658 #> 3316 13.2 2 1887 1887-01-31 10:00:01 bone 1658 #> 3317 4.2 3 1887 1887-03-02 20:00:01 blood 1659 #> 3318 4.2 3 1887 1887-03-02 20:00:01 bone 1659 #> 3319 6.9 4 1887 1887-04-02 06:00:00 blood 1660 #> 3320 6.9 4 1887 1887-04-02 06:00:00 bone 1660 #> 3321 20.0 5 1887 1887-05-02 16:00:01 blood 1661 #> 3322 20.0 5 1887 1887-05-02 16:00:01 bone 1661 #> 3323 15.7 6 1887 1887-06-02 02:00:01 blood 1662 #> 3324 15.7 6 1887 1887-06-02 02:00:01 bone 1662 #> 3325 23.3 7 1887 1887-07-02 12:00:00 blood 1663 #> 3326 23.3 7 1887 1887-07-02 12:00:00 bone 1663 #> 3327 21.4 8 1887 1887-08-01 22:00:01 blood 1664 #> 3328 21.4 8 1887 1887-08-01 22:00:01 bone 1664 #> 3329 7.4 9 1887 1887-09-01 08:00:01 blood 1665 #> 3330 7.4 9 1887 1887-09-01 08:00:01 bone 1665 #> 3331 6.6 10 1887 1887-10-01 18:00:00 blood 1666 #> 3332 6.6 10 1887 1887-10-01 18:00:00 bone 1666 #> 3333 6.9 11 1887 1887-11-01 04:00:01 blood 1667 #> 3334 6.9 11 1887 1887-11-01 04:00:01 bone 1667 #> 3335 20.7 12 1887 1887-12-01 14:00:01 blood 1668 #> 3336 20.7 12 1887 1887-12-01 14:00:01 bone 1668 #> 3337 12.7 1 1888 1888-01-01 00:00:00 blood 1669 #> 3338 12.7 1 1888 1888-01-01 00:00:00 bone 1669 #> 3339 7.1 2 1888 1888-01-31 12:00:01 blood 1670 #> 3340 7.1 2 1888 1888-01-31 12:00:01 bone 1670 #> 3341 7.8 3 1888 1888-03-02 00:00:01 blood 1671 #> 3342 7.8 3 1888 1888-03-02 00:00:01 bone 1671 #> 3343 5.1 4 1888 1888-04-01 12:00:00 blood 1672 #> 3344 5.1 4 1888 1888-04-01 12:00:00 bone 1672 #> 3345 7.0 5 1888 1888-05-02 00:00:01 blood 1673 #> 3346 7.0 5 1888 1888-05-02 00:00:01 bone 1673 #> 3347 7.1 6 1888 1888-06-01 12:00:01 blood 1674 #> 3348 7.1 6 1888 1888-06-01 12:00:01 bone 1674 #> 3349 3.1 7 1888 1888-07-02 00:00:00 blood 1675 #> 3350 3.1 7 1888 1888-07-02 00:00:00 bone 1675 #> 3351 2.8 8 1888 1888-08-01 12:00:01 blood 1676 #> 3352 2.8 8 1888 1888-08-01 12:00:01 bone 1676 #> 3353 8.8 9 1888 1888-09-01 00:00:01 blood 1677 #> 3354 8.8 9 1888 1888-09-01 00:00:01 bone 1677 #> 3355 2.1 10 1888 1888-10-01 12:00:00 blood 1678 #> 3356 2.1 10 1888 1888-10-01 12:00:00 bone 1678 #> 3357 10.7 11 1888 1888-11-01 00:00:01 blood 1679 #> 3358 10.7 11 1888 1888-11-01 00:00:01 bone 1679 #> 3359 6.7 12 1888 1888-12-01 12:00:01 blood 1680 #> 3360 6.7 12 1888 1888-12-01 12:00:01 bone 1680 #> 3361 0.8 1 1889 1889-01-01 00:00:00 blood 1681 #> 3362 0.8 1 1889 1889-01-01 00:00:00 bone 1681 #> 3363 8.5 2 1889 1889-01-31 10:00:01 blood 1682 #> 3364 8.5 2 1889 1889-01-31 10:00:01 bone 1682 #> 3365 7.0 3 1889 1889-03-02 20:00:01 blood 1683 #> 3366 7.0 3 1889 1889-03-02 20:00:01 bone 1683 #> 3367 4.3 4 1889 1889-04-02 06:00:00 blood 1684 #> 3368 4.3 4 1889 1889-04-02 06:00:00 bone 1684 #> 3369 2.4 5 1889 1889-05-02 16:00:01 blood 1685 #> 3370 2.4 5 1889 1889-05-02 16:00:01 bone 1685 #> 3371 6.4 6 1889 1889-06-02 02:00:01 blood 1686 #> 3372 6.4 6 1889 1889-06-02 02:00:01 bone 1686 #> 3373 9.7 7 1889 1889-07-02 12:00:00 blood 1687 #> 3374 9.7 7 1889 1889-07-02 12:00:00 bone 1687 #> 3375 20.6 8 1889 1889-08-01 22:00:01 blood 1688 #> 3376 20.6 8 1889 1889-08-01 22:00:01 bone 1688 #> 3377 6.5 9 1889 1889-09-01 08:00:01 blood 1689 #> 3378 6.5 9 1889 1889-09-01 08:00:01 bone 1689 #> 3379 2.1 10 1889 1889-10-01 18:00:00 blood 1690 #> 3380 2.1 10 1889 1889-10-01 18:00:00 bone 1690 #> 3381 0.2 11 1889 1889-11-01 04:00:01 blood 1691 #> 3382 0.2 11 1889 1889-11-01 04:00:01 bone 1691 #> 3383 6.7 12 1889 1889-12-01 14:00:01 blood 1692 #> 3384 6.7 12 1889 1889-12-01 14:00:01 bone 1692 #> 3385 5.3 1 1890 1890-01-01 00:00:00 blood 1693 #> 3386 5.3 1 1890 1890-01-01 00:00:00 bone 1693 #> 3387 0.6 2 1890 1890-01-31 10:00:01 blood 1694 #> 3388 0.6 2 1890 1890-01-31 10:00:01 bone 1694 #> 3389 5.1 3 1890 1890-03-02 20:00:01 blood 1695 #> 3390 5.1 3 1890 1890-03-02 20:00:01 bone 1695 #> 3391 1.6 4 1890 1890-04-02 06:00:00 blood 1696 #> 3392 1.6 4 1890 1890-04-02 06:00:00 bone 1696 #> 3393 4.8 5 1890 1890-05-02 16:00:01 blood 1697 #> 3394 4.8 5 1890 1890-05-02 16:00:01 bone 1697 #> 3395 1.3 6 1890 1890-06-02 02:00:01 blood 1698 #> 3396 1.3 6 1890 1890-06-02 02:00:01 bone 1698 #> 3397 11.6 7 1890 1890-07-02 12:00:00 blood 1699 #> 3398 11.6 7 1890 1890-07-02 12:00:00 bone 1699 #> 3399 8.5 8 1890 1890-08-01 22:00:01 blood 1700 #> 3400 8.5 8 1890 1890-08-01 22:00:01 bone 1700 #> 3401 17.2 9 1890 1890-09-01 08:00:01 blood 1701 #> 3402 17.2 9 1890 1890-09-01 08:00:01 bone 1701 #> 3403 11.2 10 1890 1890-10-01 18:00:00 blood 1702 #> 3404 11.2 10 1890 1890-10-01 18:00:00 bone 1702 #> 3405 9.6 11 1890 1890-11-01 04:00:01 blood 1703 #> 3406 9.6 11 1890 1890-11-01 04:00:01 bone 1703 #> 3407 7.8 12 1890 1890-12-01 14:00:01 blood 1704 #> 3408 7.8 12 1890 1890-12-01 14:00:01 bone 1704 #> 3409 13.5 1 1891 1891-01-01 00:00:00 blood 1705 #> 3410 13.5 1 1891 1891-01-01 00:00:00 bone 1705 #> 3411 22.2 2 1891 1891-01-31 10:00:01 blood 1706 #> 3412 22.2 2 1891 1891-01-31 10:00:01 bone 1706 #> 3413 10.4 3 1891 1891-03-02 20:00:01 blood 1707 #> 3414 10.4 3 1891 1891-03-02 20:00:01 bone 1707 #> 3415 20.5 4 1891 1891-04-02 06:00:00 blood 1708 #> 3416 20.5 4 1891 1891-04-02 06:00:00 bone 1708 #> 3417 41.1 5 1891 1891-05-02 16:00:01 blood 1709 #> 3418 41.1 5 1891 1891-05-02 16:00:01 bone 1709 #> 3419 48.3 6 1891 1891-06-02 02:00:01 blood 1710 #> 3420 48.3 6 1891 1891-06-02 02:00:01 bone 1710 #> 3421 58.8 7 1891 1891-07-02 12:00:00 blood 1711 #> 3422 58.8 7 1891 1891-07-02 12:00:00 bone 1711 #> 3423 33.2 8 1891 1891-08-01 22:00:01 blood 1712 #> 3424 33.2 8 1891 1891-08-01 22:00:01 bone 1712 #> 3425 53.8 9 1891 1891-09-01 08:00:01 blood 1713 #> 3426 53.8 9 1891 1891-09-01 08:00:01 bone 1713 #> 3427 51.5 10 1891 1891-10-01 18:00:00 blood 1714 #> 3428 51.5 10 1891 1891-10-01 18:00:00 bone 1714 #> 3429 41.9 11 1891 1891-11-01 04:00:01 blood 1715 #> 3430 41.9 11 1891 1891-11-01 04:00:01 bone 1715 #> 3431 32.3 12 1891 1891-12-01 14:00:01 blood 1716 #> 3432 32.3 12 1891 1891-12-01 14:00:01 bone 1716 #> 3433 69.1 1 1892 1892-01-01 00:00:00 blood 1717 #> 3434 69.1 1 1892 1892-01-01 00:00:00 bone 1717 #> 3435 75.6 2 1892 1892-01-31 12:00:01 blood 1718 #> 3436 75.6 2 1892 1892-01-31 12:00:01 bone 1718 #> 3437 49.9 3 1892 1892-03-02 00:00:01 blood 1719 #> 3438 49.9 3 1892 1892-03-02 00:00:01 bone 1719 #> 3439 69.6 4 1892 1892-04-01 12:00:00 blood 1720 #> 3440 69.6 4 1892 1892-04-01 12:00:00 bone 1720 #> 3441 79.6 5 1892 1892-05-02 00:00:01 blood 1721 #> 3442 79.6 5 1892 1892-05-02 00:00:01 bone 1721 #> 3443 76.3 6 1892 1892-06-01 12:00:01 blood 1722 #> 3444 76.3 6 1892 1892-06-01 12:00:01 bone 1722 #> 3445 76.8 7 1892 1892-07-02 00:00:00 blood 1723 #> 3446 76.8 7 1892 1892-07-02 00:00:00 bone 1723 #> 3447 101.4 8 1892 1892-08-01 12:00:01 blood 1724 #> 3448 101.4 8 1892 1892-08-01 12:00:01 bone 1724 #> 3449 62.8 9 1892 1892-09-01 00:00:01 blood 1725 #> 3450 62.8 9 1892 1892-09-01 00:00:01 bone 1725 #> 3451 70.5 10 1892 1892-10-01 12:00:00 blood 1726 #> 3452 70.5 10 1892 1892-10-01 12:00:00 bone 1726 #> 3453 65.4 11 1892 1892-11-01 00:00:01 blood 1727 #> 3454 65.4 11 1892 1892-11-01 00:00:01 bone 1727 #> 3455 78.6 12 1892 1892-12-01 12:00:01 blood 1728 #> 3456 78.6 12 1892 1892-12-01 12:00:01 bone 1728 #> 3457 75.0 1 1893 1893-01-01 00:00:00 blood 1729 #> 3458 75.0 1 1893 1893-01-01 00:00:00 bone 1729 #> 3459 73.0 2 1893 1893-01-31 10:00:01 blood 1730 #> 3460 73.0 2 1893 1893-01-31 10:00:01 bone 1730 #> 3461 65.7 3 1893 1893-03-02 20:00:01 blood 1731 #> 3462 65.7 3 1893 1893-03-02 20:00:01 bone 1731 #> 3463 88.1 4 1893 1893-04-02 06:00:00 blood 1732 #> 3464 88.1 4 1893 1893-04-02 06:00:00 bone 1732 #> 3465 84.7 5 1893 1893-05-02 16:00:01 blood 1733 #> 3466 84.7 5 1893 1893-05-02 16:00:01 bone 1733 #> 3467 88.2 6 1893 1893-06-02 02:00:01 blood 1734 #> 3468 88.2 6 1893 1893-06-02 02:00:01 bone 1734 #> 3469 88.8 7 1893 1893-07-02 12:00:00 blood 1735 #> 3470 88.8 7 1893 1893-07-02 12:00:00 bone 1735 #> 3471 129.2 8 1893 1893-08-01 22:00:01 blood 1736 #> 3472 129.2 8 1893 1893-08-01 22:00:01 bone 1736 #> 3473 77.9 9 1893 1893-09-01 08:00:01 blood 1737 #> 3474 77.9 9 1893 1893-09-01 08:00:01 bone 1737 #> 3475 79.7 10 1893 1893-10-01 18:00:00 blood 1738 #> 3476 79.7 10 1893 1893-10-01 18:00:00 bone 1738 #> 3477 75.1 11 1893 1893-11-01 04:00:01 blood 1739 #> 3478 75.1 11 1893 1893-11-01 04:00:01 bone 1739 #> 3479 93.8 12 1893 1893-12-01 14:00:01 blood 1740 #> 3480 93.8 12 1893 1893-12-01 14:00:01 bone 1740 #> 3481 83.2 1 1894 1894-01-01 00:00:00 blood 1741 #> 3482 83.2 1 1894 1894-01-01 00:00:00 bone 1741 #> 3483 84.6 2 1894 1894-01-31 10:00:01 blood 1742 #> 3484 84.6 2 1894 1894-01-31 10:00:01 bone 1742 #> 3485 52.3 3 1894 1894-03-02 20:00:01 blood 1743 #> 3486 52.3 3 1894 1894-03-02 20:00:01 bone 1743 #> 3487 81.6 4 1894 1894-04-02 06:00:00 blood 1744 #> 3488 81.6 4 1894 1894-04-02 06:00:00 bone 1744 #> 3489 101.2 5 1894 1894-05-02 16:00:01 blood 1745 #> 3490 101.2 5 1894 1894-05-02 16:00:01 bone 1745 #> 3491 98.9 6 1894 1894-06-02 02:00:01 blood 1746 #> 3492 98.9 6 1894 1894-06-02 02:00:01 bone 1746 #> 3493 106.0 7 1894 1894-07-02 12:00:00 blood 1747 #> 3494 106.0 7 1894 1894-07-02 12:00:00 bone 1747 #> 3495 70.3 8 1894 1894-08-01 22:00:01 blood 1748 #> 3496 70.3 8 1894 1894-08-01 22:00:01 bone 1748 #> 3497 65.9 9 1894 1894-09-01 08:00:01 blood 1749 #> 3498 65.9 9 1894 1894-09-01 08:00:01 bone 1749 #> 3499 75.5 10 1894 1894-10-01 18:00:00 blood 1750 #> 3500 75.5 10 1894 1894-10-01 18:00:00 bone 1750 #> 3501 56.6 11 1894 1894-11-01 04:00:01 blood 1751 #> 3502 56.6 11 1894 1894-11-01 04:00:01 bone 1751 #> 3503 60.0 12 1894 1894-12-01 14:00:01 blood 1752 #> 3504 60.0 12 1894 1894-12-01 14:00:01 bone 1752 #> 3505 63.3 1 1895 1895-01-01 00:00:00 blood 1753 #> 3506 63.3 1 1895 1895-01-01 00:00:00 bone 1753 #> 3507 67.2 2 1895 1895-01-31 10:00:01 blood 1754 #> 3508 67.2 2 1895 1895-01-31 10:00:01 bone 1754 #> 3509 61.0 3 1895 1895-03-02 20:00:01 blood 1755 #> 3510 61.0 3 1895 1895-03-02 20:00:01 bone 1755 #> 3511 76.9 4 1895 1895-04-02 06:00:00 blood 1756 #> 3512 76.9 4 1895 1895-04-02 06:00:00 bone 1756 #> 3513 67.5 5 1895 1895-05-02 16:00:01 blood 1757 #> 3514 67.5 5 1895 1895-05-02 16:00:01 bone 1757 #> 3515 71.5 6 1895 1895-06-02 02:00:01 blood 1758 #> 3516 71.5 6 1895 1895-06-02 02:00:01 bone 1758 #> 3517 47.8 7 1895 1895-07-02 12:00:00 blood 1759 #> 3518 47.8 7 1895 1895-07-02 12:00:00 bone 1759 #> 3519 68.9 8 1895 1895-08-01 22:00:01 blood 1760 #> 3520 68.9 8 1895 1895-08-01 22:00:01 bone 1760 #> 3521 57.7 9 1895 1895-09-01 08:00:01 blood 1761 #> 3522 57.7 9 1895 1895-09-01 08:00:01 bone 1761 #> 3523 67.9 10 1895 1895-10-01 18:00:00 blood 1762 #> 3524 67.9 10 1895 1895-10-01 18:00:00 bone 1762 #> 3525 47.2 11 1895 1895-11-01 04:00:01 blood 1763 #> 3526 47.2 11 1895 1895-11-01 04:00:01 bone 1763 #> 3527 70.7 12 1895 1895-12-01 14:00:01 blood 1764 #> 3528 70.7 12 1895 1895-12-01 14:00:01 bone 1764 #> 3529 29.0 1 1896 1896-01-01 00:00:00 blood 1765 #> 3530 29.0 1 1896 1896-01-01 00:00:00 bone 1765 #> 3531 57.4 2 1896 1896-01-31 12:00:01 blood 1766 #> 3532 57.4 2 1896 1896-01-31 12:00:01 bone 1766 #> 3533 52.0 3 1896 1896-03-02 00:00:01 blood 1767 #> 3534 52.0 3 1896 1896-03-02 00:00:01 bone 1767 #> 3535 43.8 4 1896 1896-04-01 12:00:00 blood 1768 #> 3536 43.8 4 1896 1896-04-01 12:00:00 bone 1768 #> 3537 27.7 5 1896 1896-05-02 00:00:01 blood 1769 #> 3538 27.7 5 1896 1896-05-02 00:00:01 bone 1769 #> 3539 49.0 6 1896 1896-06-01 12:00:01 blood 1770 #> 3540 49.0 6 1896 1896-06-01 12:00:01 bone 1770 #> 3541 45.0 7 1896 1896-07-02 00:00:00 blood 1771 #> 3542 45.0 7 1896 1896-07-02 00:00:00 bone 1771 #> 3543 27.2 8 1896 1896-08-01 12:00:01 blood 1772 #> 3544 27.2 8 1896 1896-08-01 12:00:01 bone 1772 #> 3545 61.3 9 1896 1896-09-01 00:00:01 blood 1773 #> 3546 61.3 9 1896 1896-09-01 00:00:01 bone 1773 #> 3547 28.4 10 1896 1896-10-01 12:00:00 blood 1774 #> 3548 28.4 10 1896 1896-10-01 12:00:00 bone 1774 #> 3549 38.0 11 1896 1896-11-01 00:00:01 blood 1775 #> 3550 38.0 11 1896 1896-11-01 00:00:01 bone 1775 #> 3551 42.6 12 1896 1896-12-01 12:00:01 blood 1776 #> 3552 42.6 12 1896 1896-12-01 12:00:01 bone 1776 #> 3553 40.6 1 1897 1897-01-01 00:00:00 blood 1777 #> 3554 40.6 1 1897 1897-01-01 00:00:00 bone 1777 #> 3555 29.4 2 1897 1897-01-31 10:00:01 blood 1778 #> 3556 29.4 2 1897 1897-01-31 10:00:01 bone 1778 #> 3557 29.1 3 1897 1897-03-02 20:00:01 blood 1779 #> 3558 29.1 3 1897 1897-03-02 20:00:01 bone 1779 #> 3559 31.0 4 1897 1897-04-02 06:00:00 blood 1780 #> 3560 31.0 4 1897 1897-04-02 06:00:00 bone 1780 #> 3561 20.0 5 1897 1897-05-02 16:00:01 blood 1781 #> 3562 20.0 5 1897 1897-05-02 16:00:01 bone 1781 #> 3563 11.3 6 1897 1897-06-02 02:00:01 blood 1782 #> 3564 11.3 6 1897 1897-06-02 02:00:01 bone 1782 #> 3565 27.6 7 1897 1897-07-02 12:00:00 blood 1783 #> 3566 27.6 7 1897 1897-07-02 12:00:00 bone 1783 #> 3567 21.8 8 1897 1897-08-01 22:00:01 blood 1784 #> 3568 21.8 8 1897 1897-08-01 22:00:01 bone 1784 #> 3569 48.1 9 1897 1897-09-01 08:00:01 blood 1785 #> 3570 48.1 9 1897 1897-09-01 08:00:01 bone 1785 #> 3571 14.3 10 1897 1897-10-01 18:00:00 blood 1786 #> 3572 14.3 10 1897 1897-10-01 18:00:00 bone 1786 #> 3573 8.4 11 1897 1897-11-01 04:00:01 blood 1787 #> 3574 8.4 11 1897 1897-11-01 04:00:01 bone 1787 #> 3575 33.3 12 1897 1897-12-01 14:00:01 blood 1788 #> 3576 33.3 12 1897 1897-12-01 14:00:01 bone 1788 #> 3577 30.2 1 1898 1898-01-01 00:00:00 blood 1789 #> 3578 30.2 1 1898 1898-01-01 00:00:00 bone 1789 #> 3579 36.4 2 1898 1898-01-31 10:00:01 blood 1790 #> 3580 36.4 2 1898 1898-01-31 10:00:01 bone 1790 #> 3581 38.3 3 1898 1898-03-02 20:00:01 blood 1791 #> 3582 38.3 3 1898 1898-03-02 20:00:01 bone 1791 #> 3583 14.5 4 1898 1898-04-02 06:00:00 blood 1792 #> 3584 14.5 4 1898 1898-04-02 06:00:00 bone 1792 #> 3585 25.8 5 1898 1898-05-02 16:00:01 blood 1793 #> 3586 25.8 5 1898 1898-05-02 16:00:01 bone 1793 #> 3587 22.3 6 1898 1898-06-02 02:00:01 blood 1794 #> 3588 22.3 6 1898 1898-06-02 02:00:01 bone 1794 #> 3589 9.0 7 1898 1898-07-02 12:00:00 blood 1795 #> 3590 9.0 7 1898 1898-07-02 12:00:00 bone 1795 #> 3591 31.4 8 1898 1898-08-01 22:00:01 blood 1796 #> 3592 31.4 8 1898 1898-08-01 22:00:01 bone 1796 #> 3593 34.8 9 1898 1898-09-01 08:00:01 blood 1797 #> 3594 34.8 9 1898 1898-09-01 08:00:01 bone 1797 #> 3595 34.4 10 1898 1898-10-01 18:00:00 blood 1798 #> 3596 34.4 10 1898 1898-10-01 18:00:00 bone 1798 #> 3597 30.9 11 1898 1898-11-01 04:00:01 blood 1799 #> 3598 30.9 11 1898 1898-11-01 04:00:01 bone 1799 #> 3599 12.6 12 1898 1898-12-01 14:00:01 blood 1800 #> 3600 12.6 12 1898 1898-12-01 14:00:01 bone 1800 #> 3601 19.5 1 1899 1899-01-01 00:00:00 blood 1801 #> 3602 19.5 1 1899 1899-01-01 00:00:00 bone 1801 #> 3603 9.2 2 1899 1899-01-31 10:00:01 blood 1802 #> 3604 9.2 2 1899 1899-01-31 10:00:01 bone 1802 #> 3605 18.1 3 1899 1899-03-02 20:00:01 blood 1803 #> 3606 18.1 3 1899 1899-03-02 20:00:01 bone 1803 #> 3607 14.2 4 1899 1899-04-02 06:00:00 blood 1804 #> 3608 14.2 4 1899 1899-04-02 06:00:00 bone 1804 #> 3609 7.7 5 1899 1899-05-02 16:00:01 blood 1805 #> 3610 7.7 5 1899 1899-05-02 16:00:01 bone 1805 #> 3611 20.5 6 1899 1899-06-02 02:00:01 blood 1806 #> 3612 20.5 6 1899 1899-06-02 02:00:01 bone 1806 #> 3613 13.5 7 1899 1899-07-02 12:00:00 blood 1807 #> 3614 13.5 7 1899 1899-07-02 12:00:00 bone 1807 #> 3615 2.9 8 1899 1899-08-01 22:00:01 blood 1808 #> 3616 2.9 8 1899 1899-08-01 22:00:01 bone 1808 #> 3617 8.4 9 1899 1899-09-01 08:00:01 blood 1809 #> 3618 8.4 9 1899 1899-09-01 08:00:01 bone 1809 #> 3619 13.0 10 1899 1899-10-01 18:00:00 blood 1810 #> 3620 13.0 10 1899 1899-10-01 18:00:00 bone 1810 #> 3621 7.8 11 1899 1899-11-01 04:00:01 blood 1811 #> 3622 7.8 11 1899 1899-11-01 04:00:01 bone 1811 #> 3623 10.5 12 1899 1899-12-01 14:00:01 blood 1812 #> 3624 10.5 12 1899 1899-12-01 14:00:01 bone 1812 #> 3625 9.4 1 1900 1900-01-01 00:00:00 blood 1813 #> 3626 9.4 1 1900 1900-01-01 00:00:00 bone 1813 #> 3627 13.6 2 1900 1900-01-31 10:00:01 blood 1814 #> 3628 13.6 2 1900 1900-01-31 10:00:01 bone 1814 #> 3629 8.6 3 1900 1900-03-02 20:00:01 blood 1815 #> 3630 8.6 3 1900 1900-03-02 20:00:01 bone 1815 #> 3631 16.0 4 1900 1900-04-02 06:00:00 blood 1816 #> 3632 16.0 4 1900 1900-04-02 06:00:00 bone 1816 #> 3633 15.2 5 1900 1900-05-02 16:00:01 blood 1817 #> 3634 15.2 5 1900 1900-05-02 16:00:01 bone 1817 #> 3635 12.1 6 1900 1900-06-02 02:00:01 blood 1818 #> 3636 12.1 6 1900 1900-06-02 02:00:01 bone 1818 #> 3637 8.3 7 1900 1900-07-02 12:00:00 blood 1819 #> 3638 8.3 7 1900 1900-07-02 12:00:00 bone 1819 #> 3639 4.3 8 1900 1900-08-01 22:00:01 blood 1820 #> 3640 4.3 8 1900 1900-08-01 22:00:01 bone 1820 #> 3641 8.3 9 1900 1900-09-01 08:00:01 blood 1821 #> 3642 8.3 9 1900 1900-09-01 08:00:01 bone 1821 #> 3643 12.9 10 1900 1900-10-01 18:00:00 blood 1822 #> 3644 12.9 10 1900 1900-10-01 18:00:00 bone 1822 #> 3645 4.5 11 1900 1900-11-01 04:00:01 blood 1823 #> 3646 4.5 11 1900 1900-11-01 04:00:01 bone 1823 #> 3647 0.3 12 1900 1900-12-01 14:00:01 blood 1824 #> 3648 0.3 12 1900 1900-12-01 14:00:01 bone 1824 #> 3649 0.2 1 1901 1901-01-01 00:00:00 blood 1825 #> 3650 0.2 1 1901 1901-01-01 00:00:00 bone 1825 #> 3651 2.4 2 1901 1901-01-31 10:00:01 blood 1826 #> 3652 2.4 2 1901 1901-01-31 10:00:01 bone 1826 #> 3653 4.5 3 1901 1901-03-02 20:00:01 blood 1827 #> 3654 4.5 3 1901 1901-03-02 20:00:01 bone 1827 #> 3655 0.0 4 1901 1901-04-02 06:00:00 blood 1828 #> 3656 0.0 4 1901 1901-04-02 06:00:00 bone 1828 #> 3657 10.2 5 1901 1901-05-02 16:00:01 blood 1829 #> 3658 10.2 5 1901 1901-05-02 16:00:01 bone 1829 #> 3659 5.8 6 1901 1901-06-02 02:00:01 blood 1830 #> 3660 5.8 6 1901 1901-06-02 02:00:01 bone 1830 #> 3661 0.7 7 1901 1901-07-02 12:00:00 blood 1831 #> 3662 0.7 7 1901 1901-07-02 12:00:00 bone 1831 #> 3663 1.0 8 1901 1901-08-01 22:00:01 blood 1832 #> 3664 1.0 8 1901 1901-08-01 22:00:01 bone 1832 #> 3665 0.6 9 1901 1901-09-01 08:00:01 blood 1833 #> 3666 0.6 9 1901 1901-09-01 08:00:01 bone 1833 #> 3667 3.7 10 1901 1901-10-01 18:00:00 blood 1834 #> 3668 3.7 10 1901 1901-10-01 18:00:00 bone 1834 #> 3669 3.8 11 1901 1901-11-01 04:00:01 blood 1835 #> 3670 3.8 11 1901 1901-11-01 04:00:01 bone 1835 #> 3671 0.0 12 1901 1901-12-01 14:00:01 blood 1836 #> 3672 0.0 12 1901 1901-12-01 14:00:01 bone 1836 #> 3673 5.2 1 1902 1902-01-01 00:00:00 blood 1837 #> 3674 5.2 1 1902 1902-01-01 00:00:00 bone 1837 #> 3675 0.0 2 1902 1902-01-31 10:00:01 blood 1838 #> 3676 0.0 2 1902 1902-01-31 10:00:01 bone 1838 #> 3677 12.4 3 1902 1902-03-02 20:00:01 blood 1839 #> 3678 12.4 3 1902 1902-03-02 20:00:01 bone 1839 #> 3679 0.0 4 1902 1902-04-02 06:00:00 blood 1840 #> 3680 0.0 4 1902 1902-04-02 06:00:00 bone 1840 #> 3681 2.8 5 1902 1902-05-02 16:00:01 blood 1841 #> 3682 2.8 5 1902 1902-05-02 16:00:01 bone 1841 #> 3683 1.4 6 1902 1902-06-02 02:00:01 blood 1842 #> 3684 1.4 6 1902 1902-06-02 02:00:01 bone 1842 #> 3685 0.9 7 1902 1902-07-02 12:00:00 blood 1843 #> 3686 0.9 7 1902 1902-07-02 12:00:00 bone 1843 #> 3687 2.3 8 1902 1902-08-01 22:00:01 blood 1844 #> 3688 2.3 8 1902 1902-08-01 22:00:01 bone 1844 #> 3689 7.6 9 1902 1902-09-01 08:00:01 blood 1845 #> 3690 7.6 9 1902 1902-09-01 08:00:01 bone 1845 #> 3691 16.3 10 1902 1902-10-01 18:00:00 blood 1846 #> 3692 16.3 10 1902 1902-10-01 18:00:00 bone 1846 #> 3693 10.3 11 1902 1902-11-01 04:00:01 blood 1847 #> 3694 10.3 11 1902 1902-11-01 04:00:01 bone 1847 #> 3695 1.1 12 1902 1902-12-01 14:00:01 blood 1848 #> 3696 1.1 12 1902 1902-12-01 14:00:01 bone 1848 #> 3697 8.3 1 1903 1903-01-01 00:00:00 blood 1849 #> 3698 8.3 1 1903 1903-01-01 00:00:00 bone 1849 #> 3699 17.0 2 1903 1903-01-31 10:00:01 blood 1850 #> 3700 17.0 2 1903 1903-01-31 10:00:01 bone 1850 #> 3701 13.5 3 1903 1903-03-02 20:00:01 blood 1851 #> 3702 13.5 3 1903 1903-03-02 20:00:01 bone 1851 #> 3703 26.1 4 1903 1903-04-02 06:00:00 blood 1852 #> 3704 26.1 4 1903 1903-04-02 06:00:00 bone 1852 #> 3705 14.6 5 1903 1903-05-02 16:00:01 blood 1853 #> 3706 14.6 5 1903 1903-05-02 16:00:01 bone 1853 #> 3707 16.3 6 1903 1903-06-02 02:00:01 blood 1854 #> 3708 16.3 6 1903 1903-06-02 02:00:01 bone 1854 #> 3709 27.9 7 1903 1903-07-02 12:00:00 blood 1855 #> 3710 27.9 7 1903 1903-07-02 12:00:00 bone 1855 #> 3711 28.8 8 1903 1903-08-01 22:00:01 blood 1856 #> 3712 28.8 8 1903 1903-08-01 22:00:01 bone 1856 #> 3713 11.1 9 1903 1903-09-01 08:00:01 blood 1857 #> 3714 11.1 9 1903 1903-09-01 08:00:01 bone 1857 #> 3715 38.9 10 1903 1903-10-01 18:00:00 blood 1858 #> 3716 38.9 10 1903 1903-10-01 18:00:00 bone 1858 #> 3717 44.5 11 1903 1903-11-01 04:00:01 blood 1859 #> 3718 44.5 11 1903 1903-11-01 04:00:01 bone 1859 #> 3719 45.6 12 1903 1903-12-01 14:00:01 blood 1860 #> 3720 45.6 12 1903 1903-12-01 14:00:01 bone 1860 #> 3721 31.6 1 1904 1904-01-01 00:00:00 blood 1861 #> 3722 31.6 1 1904 1904-01-01 00:00:00 bone 1861 #> 3723 24.5 2 1904 1904-01-31 12:00:01 blood 1862 #> 3724 24.5 2 1904 1904-01-31 12:00:01 bone 1862 #> 3725 37.2 3 1904 1904-03-02 00:00:01 blood 1863 #> 3726 37.2 3 1904 1904-03-02 00:00:01 bone 1863 #> 3727 43.0 4 1904 1904-04-01 12:00:00 blood 1864 #> 3728 43.0 4 1904 1904-04-01 12:00:00 bone 1864 #> 3729 39.5 5 1904 1904-05-02 00:00:01 blood 1865 #> 3730 39.5 5 1904 1904-05-02 00:00:01 bone 1865 #> 3731 41.9 6 1904 1904-06-01 12:00:01 blood 1866 #> 3732 41.9 6 1904 1904-06-01 12:00:01 bone 1866 #> 3733 50.6 7 1904 1904-07-02 00:00:00 blood 1867 #> 3734 50.6 7 1904 1904-07-02 00:00:00 bone 1867 #> 3735 58.2 8 1904 1904-08-01 12:00:01 blood 1868 #> 3736 58.2 8 1904 1904-08-01 12:00:01 bone 1868 #> 3737 30.1 9 1904 1904-09-01 00:00:01 blood 1869 #> 3738 30.1 9 1904 1904-09-01 00:00:01 bone 1869 #> 3739 54.2 10 1904 1904-10-01 12:00:00 blood 1870 #> 3740 54.2 10 1904 1904-10-01 12:00:00 bone 1870 #> 3741 38.0 11 1904 1904-11-01 00:00:01 blood 1871 #> 3742 38.0 11 1904 1904-11-01 00:00:01 bone 1871 #> 3743 54.6 12 1904 1904-12-01 12:00:01 blood 1872 #> 3744 54.6 12 1904 1904-12-01 12:00:01 bone 1872 #> 3745 54.8 1 1905 1905-01-01 00:00:00 blood 1873 #> 3746 54.8 1 1905 1905-01-01 00:00:00 bone 1873 #> 3747 85.8 2 1905 1905-01-31 10:00:01 blood 1874 #> 3748 85.8 2 1905 1905-01-31 10:00:01 bone 1874 #> 3749 56.5 3 1905 1905-03-02 20:00:01 blood 1875 #> 3750 56.5 3 1905 1905-03-02 20:00:01 bone 1875 #> 3751 39.3 4 1905 1905-04-02 06:00:00 blood 1876 #> 3752 39.3 4 1905 1905-04-02 06:00:00 bone 1876 #> 3753 48.0 5 1905 1905-05-02 16:00:01 blood 1877 #> 3754 48.0 5 1905 1905-05-02 16:00:01 bone 1877 #> 3755 49.0 6 1905 1905-06-02 02:00:01 blood 1878 #> 3756 49.0 6 1905 1905-06-02 02:00:01 bone 1878 #> 3757 73.0 7 1905 1905-07-02 12:00:00 blood 1879 #> 3758 73.0 7 1905 1905-07-02 12:00:00 bone 1879 #> 3759 58.8 8 1905 1905-08-01 22:00:01 blood 1880 #> 3760 58.8 8 1905 1905-08-01 22:00:01 bone 1880 #> 3761 55.0 9 1905 1905-09-01 08:00:01 blood 1881 #> 3762 55.0 9 1905 1905-09-01 08:00:01 bone 1881 #> 3763 78.7 10 1905 1905-10-01 18:00:00 blood 1882 #> 3764 78.7 10 1905 1905-10-01 18:00:00 bone 1882 #> 3765 107.2 11 1905 1905-11-01 04:00:01 blood 1883 #> 3766 107.2 11 1905 1905-11-01 04:00:01 bone 1883 #> 3767 55.5 12 1905 1905-12-01 14:00:01 blood 1884 #> 3768 55.5 12 1905 1905-12-01 14:00:01 bone 1884 #> 3769 45.5 1 1906 1906-01-01 00:00:00 blood 1885 #> 3770 45.5 1 1906 1906-01-01 00:00:00 bone 1885 #> 3771 31.3 2 1906 1906-01-31 10:00:01 blood 1886 #> 3772 31.3 2 1906 1906-01-31 10:00:01 bone 1886 #> 3773 64.5 3 1906 1906-03-02 20:00:01 blood 1887 #> 3774 64.5 3 1906 1906-03-02 20:00:01 bone 1887 #> 3775 55.3 4 1906 1906-04-02 06:00:00 blood 1888 #> 3776 55.3 4 1906 1906-04-02 06:00:00 bone 1888 #> 3777 57.7 5 1906 1906-05-02 16:00:01 blood 1889 #> 3778 57.7 5 1906 1906-05-02 16:00:01 bone 1889 #> 3779 63.2 6 1906 1906-06-02 02:00:01 blood 1890 #> 3780 63.2 6 1906 1906-06-02 02:00:01 bone 1890 #> 3781 103.6 7 1906 1906-07-02 12:00:00 blood 1891 #> 3782 103.6 7 1906 1906-07-02 12:00:00 bone 1891 #> 3783 47.7 8 1906 1906-08-01 22:00:01 blood 1892 #> 3784 47.7 8 1906 1906-08-01 22:00:01 bone 1892 #> 3785 56.1 9 1906 1906-09-01 08:00:01 blood 1893 #> 3786 56.1 9 1906 1906-09-01 08:00:01 bone 1893 #> 3787 17.8 10 1906 1906-10-01 18:00:00 blood 1894 #> 3788 17.8 10 1906 1906-10-01 18:00:00 bone 1894 #> 3789 38.9 11 1906 1906-11-01 04:00:01 blood 1895 #> 3790 38.9 11 1906 1906-11-01 04:00:01 bone 1895 #> 3791 64.7 12 1906 1906-12-01 14:00:01 blood 1896 #> 3792 64.7 12 1906 1906-12-01 14:00:01 bone 1896 #> 3793 76.4 1 1907 1907-01-01 00:00:00 blood 1897 #> 3794 76.4 1 1907 1907-01-01 00:00:00 bone 1897 #> 3795 108.2 2 1907 1907-01-31 10:00:01 blood 1898 #> 3796 108.2 2 1907 1907-01-31 10:00:01 bone 1898 #> 3797 60.7 3 1907 1907-03-02 20:00:01 blood 1899 #> 3798 60.7 3 1907 1907-03-02 20:00:01 bone 1899 #> 3799 52.6 4 1907 1907-04-02 06:00:00 blood 1900 #> 3800 52.6 4 1907 1907-04-02 06:00:00 bone 1900 #> 3801 42.9 5 1907 1907-05-02 16:00:01 blood 1901 #> 3802 42.9 5 1907 1907-05-02 16:00:01 bone 1901 #> 3803 40.4 6 1907 1907-06-02 02:00:01 blood 1902 #> 3804 40.4 6 1907 1907-06-02 02:00:01 bone 1902 #> 3805 49.7 7 1907 1907-07-02 12:00:00 blood 1903 #> 3806 49.7 7 1907 1907-07-02 12:00:00 bone 1903 #> 3807 54.3 8 1907 1907-08-01 22:00:01 blood 1904 #> 3808 54.3 8 1907 1907-08-01 22:00:01 bone 1904 #> 3809 85.0 9 1907 1907-09-01 08:00:01 blood 1905 #> 3810 85.0 9 1907 1907-09-01 08:00:01 bone 1905 #> 3811 65.4 10 1907 1907-10-01 18:00:00 blood 1906 #> 3812 65.4 10 1907 1907-10-01 18:00:00 bone 1906 #> 3813 61.5 11 1907 1907-11-01 04:00:01 blood 1907 #> 3814 61.5 11 1907 1907-11-01 04:00:01 bone 1907 #> 3815 47.3 12 1907 1907-12-01 14:00:01 blood 1908 #> 3816 47.3 12 1907 1907-12-01 14:00:01 bone 1908 #> 3817 39.2 1 1908 1908-01-01 00:00:00 blood 1909 #> 3818 39.2 1 1908 1908-01-01 00:00:00 bone 1909 #> 3819 33.9 2 1908 1908-01-31 12:00:01 blood 1910 #> 3820 33.9 2 1908 1908-01-31 12:00:01 bone 1910 #> 3821 28.7 3 1908 1908-03-02 00:00:01 blood 1911 #> 3822 28.7 3 1908 1908-03-02 00:00:01 bone 1911 #> 3823 57.6 4 1908 1908-04-01 12:00:00 blood 1912 #> 3824 57.6 4 1908 1908-04-01 12:00:00 bone 1912 #> 3825 40.8 5 1908 1908-05-02 00:00:01 blood 1913 #> 3826 40.8 5 1908 1908-05-02 00:00:01 bone 1913 #> 3827 48.1 6 1908 1908-06-01 12:00:01 blood 1914 #> 3828 48.1 6 1908 1908-06-01 12:00:01 bone 1914 #> 3829 39.5 7 1908 1908-07-02 00:00:00 blood 1915 #> 3830 39.5 7 1908 1908-07-02 00:00:00 bone 1915 #> 3831 90.5 8 1908 1908-08-01 12:00:01 blood 1916 #> 3832 90.5 8 1908 1908-08-01 12:00:01 bone 1916 #> 3833 86.9 9 1908 1908-09-01 00:00:01 blood 1917 #> 3834 86.9 9 1908 1908-09-01 00:00:01 bone 1917 #> 3835 32.3 10 1908 1908-10-01 12:00:00 blood 1918 #> 3836 32.3 10 1908 1908-10-01 12:00:00 bone 1918 #> 3837 45.5 11 1908 1908-11-01 00:00:01 blood 1919 #> 3838 45.5 11 1908 1908-11-01 00:00:01 bone 1919 #> 3839 39.5 12 1908 1908-12-01 12:00:01 blood 1920 #> 3840 39.5 12 1908 1908-12-01 12:00:01 bone 1920 #> 3841 56.7 1 1909 1909-01-01 00:00:00 blood 1921 #> 3842 56.7 1 1909 1909-01-01 00:00:00 bone 1921 #> 3843 46.6 2 1909 1909-01-31 10:00:01 blood 1922 #> 3844 46.6 2 1909 1909-01-31 10:00:01 bone 1922 #> 3845 66.3 3 1909 1909-03-02 20:00:01 blood 1923 #> 3846 66.3 3 1909 1909-03-02 20:00:01 bone 1923 #> 3847 32.3 4 1909 1909-04-02 06:00:00 blood 1924 #> 3848 32.3 4 1909 1909-04-02 06:00:00 bone 1924 #> 3849 36.0 5 1909 1909-05-02 16:00:01 blood 1925 #> 3850 36.0 5 1909 1909-05-02 16:00:01 bone 1925 #> 3851 22.6 6 1909 1909-06-02 02:00:01 blood 1926 #> 3852 22.6 6 1909 1909-06-02 02:00:01 bone 1926 #> 3853 35.8 7 1909 1909-07-02 12:00:00 blood 1927 #> 3854 35.8 7 1909 1909-07-02 12:00:00 bone 1927 #> 3855 23.1 8 1909 1909-08-01 22:00:01 blood 1928 #> 3856 23.1 8 1909 1909-08-01 22:00:01 bone 1928 #> 3857 38.8 9 1909 1909-09-01 08:00:01 blood 1929 #> 3858 38.8 9 1909 1909-09-01 08:00:01 bone 1929 #> 3859 58.4 10 1909 1909-10-01 18:00:00 blood 1930 #> 3860 58.4 10 1909 1909-10-01 18:00:00 bone 1930 #> 3861 55.8 11 1909 1909-11-01 04:00:01 blood 1931 #> 3862 55.8 11 1909 1909-11-01 04:00:01 bone 1931 #> 3863 54.2 12 1909 1909-12-01 14:00:01 blood 1932 #> 3864 54.2 12 1909 1909-12-01 14:00:01 bone 1932 #> 3865 26.4 1 1910 1910-01-01 00:00:00 blood 1933 #> 3866 26.4 1 1910 1910-01-01 00:00:00 bone 1933 #> 3867 31.5 2 1910 1910-01-31 10:00:01 blood 1934 #> 3868 31.5 2 1910 1910-01-31 10:00:01 bone 1934 #> 3869 21.4 3 1910 1910-03-02 20:00:01 blood 1935 #> 3870 21.4 3 1910 1910-03-02 20:00:01 bone 1935 #> 3871 8.4 4 1910 1910-04-02 06:00:00 blood 1936 #> 3872 8.4 4 1910 1910-04-02 06:00:00 bone 1936 #> 3873 22.2 5 1910 1910-05-02 16:00:01 blood 1937 #> 3874 22.2 5 1910 1910-05-02 16:00:01 bone 1937 #> 3875 12.3 6 1910 1910-06-02 02:00:01 blood 1938 #> 3876 12.3 6 1910 1910-06-02 02:00:01 bone 1938 #> 3877 14.1 7 1910 1910-07-02 12:00:00 blood 1939 #> 3878 14.1 7 1910 1910-07-02 12:00:00 bone 1939 #> 3879 11.5 8 1910 1910-08-01 22:00:01 blood 1940 #> 3880 11.5 8 1910 1910-08-01 22:00:01 bone 1940 #> 3881 26.2 9 1910 1910-09-01 08:00:01 blood 1941 #> 3882 26.2 9 1910 1910-09-01 08:00:01 bone 1941 #> 3883 38.3 10 1910 1910-10-01 18:00:00 blood 1942 #> 3884 38.3 10 1910 1910-10-01 18:00:00 bone 1942 #> 3885 4.9 11 1910 1910-11-01 04:00:01 blood 1943 #> 3886 4.9 11 1910 1910-11-01 04:00:01 bone 1943 #> 3887 5.8 12 1910 1910-12-01 14:00:01 blood 1944 #> 3888 5.8 12 1910 1910-12-01 14:00:01 bone 1944 #> 3889 3.4 1 1911 1911-01-01 00:00:00 blood 1945 #> 3890 3.4 1 1911 1911-01-01 00:00:00 bone 1945 #> 3891 9.0 2 1911 1911-01-31 10:00:01 blood 1946 #> 3892 9.0 2 1911 1911-01-31 10:00:01 bone 1946 #> 3893 7.8 3 1911 1911-03-02 20:00:01 blood 1947 #> 3894 7.8 3 1911 1911-03-02 20:00:01 bone 1947 #> 3895 16.5 4 1911 1911-04-02 06:00:00 blood 1948 #> 3896 16.5 4 1911 1911-04-02 06:00:00 bone 1948 #> 3897 9.0 5 1911 1911-05-02 16:00:01 blood 1949 #> 3898 9.0 5 1911 1911-05-02 16:00:01 bone 1949 #> 3899 2.2 6 1911 1911-06-02 02:00:01 blood 1950 #> 3900 2.2 6 1911 1911-06-02 02:00:01 bone 1950 #> 3901 3.5 7 1911 1911-07-02 12:00:00 blood 1951 #> 3902 3.5 7 1911 1911-07-02 12:00:00 bone 1951 #> 3903 4.0 8 1911 1911-08-01 22:00:01 blood 1952 #> 3904 4.0 8 1911 1911-08-01 22:00:01 bone 1952 #> 3905 4.0 9 1911 1911-09-01 08:00:01 blood 1953 #> 3906 4.0 9 1911 1911-09-01 08:00:01 bone 1953 #> 3907 2.6 10 1911 1911-10-01 18:00:00 blood 1954 #> 3908 2.6 10 1911 1911-10-01 18:00:00 bone 1954 #> 3909 4.2 11 1911 1911-11-01 04:00:01 blood 1955 #> 3910 4.2 11 1911 1911-11-01 04:00:01 bone 1955 #> 3911 2.2 12 1911 1911-12-01 14:00:01 blood 1956 #> 3912 2.2 12 1911 1911-12-01 14:00:01 bone 1956 #> 3913 0.3 1 1912 1912-01-01 00:00:00 blood 1957 #> 3914 0.3 1 1912 1912-01-01 00:00:00 bone 1957 #> 3915 0.0 2 1912 1912-01-31 12:00:01 blood 1958 #> 3916 0.0 2 1912 1912-01-31 12:00:01 bone 1958 #> 3917 4.9 3 1912 1912-03-02 00:00:01 blood 1959 #> 3918 4.9 3 1912 1912-03-02 00:00:01 bone 1959 #> 3919 4.5 4 1912 1912-04-01 12:00:00 blood 1960 #> 3920 4.5 4 1912 1912-04-01 12:00:00 bone 1960 #> 3921 4.4 5 1912 1912-05-02 00:00:01 blood 1961 #> 3922 4.4 5 1912 1912-05-02 00:00:01 bone 1961 #> 3923 4.1 6 1912 1912-06-01 12:00:01 blood 1962 #> 3924 4.1 6 1912 1912-06-01 12:00:01 bone 1962 #> 3925 3.0 7 1912 1912-07-02 00:00:00 blood 1963 #> 3926 3.0 7 1912 1912-07-02 00:00:00 bone 1963 #> 3927 0.3 8 1912 1912-08-01 12:00:01 blood 1964 #> 3928 0.3 8 1912 1912-08-01 12:00:01 bone 1964 #> 3929 9.5 9 1912 1912-09-01 00:00:01 blood 1965 #> 3930 9.5 9 1912 1912-09-01 00:00:01 bone 1965 #> 3931 4.6 10 1912 1912-10-01 12:00:00 blood 1966 #> 3932 4.6 10 1912 1912-10-01 12:00:00 bone 1966 #> 3933 1.1 11 1912 1912-11-01 00:00:01 blood 1967 #> 3934 1.1 11 1912 1912-11-01 00:00:01 bone 1967 #> 3935 6.4 12 1912 1912-12-01 12:00:01 blood 1968 #> 3936 6.4 12 1912 1912-12-01 12:00:01 bone 1968 #> 3937 2.3 1 1913 1913-01-01 00:00:00 blood 1969 #> 3938 2.3 1 1913 1913-01-01 00:00:00 bone 1969 #> 3939 2.9 2 1913 1913-01-31 10:00:01 blood 1970 #> 3940 2.9 2 1913 1913-01-31 10:00:01 bone 1970 #> 3941 0.5 3 1913 1913-03-02 20:00:01 blood 1971 #> 3942 0.5 3 1913 1913-03-02 20:00:01 bone 1971 #> 3943 0.9 4 1913 1913-04-02 06:00:00 blood 1972 #> 3944 0.9 4 1913 1913-04-02 06:00:00 bone 1972 #> 3945 0.0 5 1913 1913-05-02 16:00:01 blood 1973 #> 3946 0.0 5 1913 1913-05-02 16:00:01 bone 1973 #> 3947 0.0 6 1913 1913-06-02 02:00:01 blood 1974 #> 3948 0.0 6 1913 1913-06-02 02:00:01 bone 1974 #> 3949 1.7 7 1913 1913-07-02 12:00:00 blood 1975 #> 3950 1.7 7 1913 1913-07-02 12:00:00 bone 1975 #> 3951 0.2 8 1913 1913-08-01 22:00:01 blood 1976 #> 3952 0.2 8 1913 1913-08-01 22:00:01 bone 1976 #> 3953 1.2 9 1913 1913-09-01 08:00:01 blood 1977 #> 3954 1.2 9 1913 1913-09-01 08:00:01 bone 1977 #> 3955 3.1 10 1913 1913-10-01 18:00:00 blood 1978 #> 3956 3.1 10 1913 1913-10-01 18:00:00 bone 1978 #> 3957 0.7 11 1913 1913-11-01 04:00:01 blood 1979 #> 3958 0.7 11 1913 1913-11-01 04:00:01 bone 1979 #> 3959 3.8 12 1913 1913-12-01 14:00:01 blood 1980 #> 3960 3.8 12 1913 1913-12-01 14:00:01 bone 1980 #> 3961 2.8 1 1914 1914-01-01 00:00:00 blood 1981 #> 3962 2.8 1 1914 1914-01-01 00:00:00 bone 1981 #> 3963 2.6 2 1914 1914-01-31 10:00:01 blood 1982 #> 3964 2.6 2 1914 1914-01-31 10:00:01 bone 1982 #> 3965 3.1 3 1914 1914-03-02 20:00:01 blood 1983 #> 3966 3.1 3 1914 1914-03-02 20:00:01 bone 1983 #> 3967 17.3 4 1914 1914-04-02 06:00:00 blood 1984 #> 3968 17.3 4 1914 1914-04-02 06:00:00 bone 1984 #> 3969 5.2 5 1914 1914-05-02 16:00:01 blood 1985 #> 3970 5.2 5 1914 1914-05-02 16:00:01 bone 1985 #> 3971 11.4 6 1914 1914-06-02 02:00:01 blood 1986 #> 3972 11.4 6 1914 1914-06-02 02:00:01 bone 1986 #> 3973 5.4 7 1914 1914-07-02 12:00:00 blood 1987 #> 3974 5.4 7 1914 1914-07-02 12:00:00 bone 1987 #> 3975 7.7 8 1914 1914-08-01 22:00:01 blood 1988 #> 3976 7.7 8 1914 1914-08-01 22:00:01 bone 1988 #> 3977 12.7 9 1914 1914-09-01 08:00:01 blood 1989 #> 3978 12.7 9 1914 1914-09-01 08:00:01 bone 1989 #> 3979 8.2 10 1914 1914-10-01 18:00:00 blood 1990 #> 3980 8.2 10 1914 1914-10-01 18:00:00 bone 1990 #> 3981 16.4 11 1914 1914-11-01 04:00:01 blood 1991 #> 3982 16.4 11 1914 1914-11-01 04:00:01 bone 1991 #> 3983 22.3 12 1914 1914-12-01 14:00:01 blood 1992 #> 3984 22.3 12 1914 1914-12-01 14:00:01 bone 1992 #> 3985 23.0 1 1915 1915-01-01 00:00:00 blood 1993 #> 3986 23.0 1 1915 1915-01-01 00:00:00 bone 1993 #> 3987 42.3 2 1915 1915-01-31 10:00:01 blood 1994 #> 3988 42.3 2 1915 1915-01-31 10:00:01 bone 1994 #> 3989 38.8 3 1915 1915-03-02 20:00:01 blood 1995 #> 3990 38.8 3 1915 1915-03-02 20:00:01 bone 1995 #> 3991 41.3 4 1915 1915-04-02 06:00:00 blood 1996 #> 3992 41.3 4 1915 1915-04-02 06:00:00 bone 1996 #> 3993 33.0 5 1915 1915-05-02 16:00:01 blood 1997 #> 3994 33.0 5 1915 1915-05-02 16:00:01 bone 1997 #> 3995 68.8 6 1915 1915-06-02 02:00:01 blood 1998 #> 3996 68.8 6 1915 1915-06-02 02:00:01 bone 1998 #> 3997 71.6 7 1915 1915-07-02 12:00:00 blood 1999 #> 3998 71.6 7 1915 1915-07-02 12:00:00 bone 1999 #> 3999 69.6 8 1915 1915-08-01 22:00:01 blood 2000 #> 4000 69.6 8 1915 1915-08-01 22:00:01 bone 2000 #> 4001 49.5 9 1915 1915-09-01 08:00:01 blood 2001 #> 4002 49.5 9 1915 1915-09-01 08:00:01 bone 2001 #> 4003 53.5 10 1915 1915-10-01 18:00:00 blood 2002 #> 4004 53.5 10 1915 1915-10-01 18:00:00 bone 2002 #> 4005 42.5 11 1915 1915-11-01 04:00:01 blood 2003 #> 4006 42.5 11 1915 1915-11-01 04:00:01 bone 2003 #> 4007 34.5 12 1915 1915-12-01 14:00:01 blood 2004 #> 4008 34.5 12 1915 1915-12-01 14:00:01 bone 2004 #> 4009 45.3 1 1916 1916-01-01 00:00:00 blood 2005 #> 4010 45.3 1 1916 1916-01-01 00:00:00 bone 2005 #> 4011 55.4 2 1916 1916-01-31 12:00:01 blood 2006 #> 4012 55.4 2 1916 1916-01-31 12:00:01 bone 2006 #> 4013 67.0 3 1916 1916-03-02 00:00:01 blood 2007 #> 4014 67.0 3 1916 1916-03-02 00:00:01 bone 2007 #> 4015 71.8 4 1916 1916-04-01 12:00:00 blood 2008 #> 4016 71.8 4 1916 1916-04-01 12:00:00 bone 2008 #> 4017 74.5 5 1916 1916-05-02 00:00:01 blood 2009 #> 4018 74.5 5 1916 1916-05-02 00:00:01 bone 2009 #> 4019 67.7 6 1916 1916-06-01 12:00:01 blood 2010 #> 4020 67.7 6 1916 1916-06-01 12:00:01 bone 2010 #> 4021 53.5 7 1916 1916-07-02 00:00:00 blood 2011 #> 4022 53.5 7 1916 1916-07-02 00:00:00 bone 2011 #> 4023 35.2 8 1916 1916-08-01 12:00:01 blood 2012 #> 4024 35.2 8 1916 1916-08-01 12:00:01 bone 2012 #> 4025 45.1 9 1916 1916-09-01 00:00:01 blood 2013 #> 4026 45.1 9 1916 1916-09-01 00:00:01 bone 2013 #> 4027 50.7 10 1916 1916-10-01 12:00:00 blood 2014 #> 4028 50.7 10 1916 1916-10-01 12:00:00 bone 2014 #> 4029 65.6 11 1916 1916-11-01 00:00:01 blood 2015 #> 4030 65.6 11 1916 1916-11-01 00:00:01 bone 2015 #> 4031 53.0 12 1916 1916-12-01 12:00:01 blood 2016 #> 4032 53.0 12 1916 1916-12-01 12:00:01 bone 2016 #> 4033 74.7 1 1917 1917-01-01 00:00:00 blood 2017 #> 4034 74.7 1 1917 1917-01-01 00:00:00 bone 2017 #> 4035 71.9 2 1917 1917-01-31 10:00:01 blood 2018 #> 4036 71.9 2 1917 1917-01-31 10:00:01 bone 2018 #> 4037 94.8 3 1917 1917-03-02 20:00:01 blood 2019 #> 4038 94.8 3 1917 1917-03-02 20:00:01 bone 2019 #> 4039 74.7 4 1917 1917-04-02 06:00:00 blood 2020 #> 4040 74.7 4 1917 1917-04-02 06:00:00 bone 2020 #> 4041 114.1 5 1917 1917-05-02 16:00:01 blood 2021 #> 4042 114.1 5 1917 1917-05-02 16:00:01 bone 2021 #> 4043 114.9 6 1917 1917-06-02 02:00:01 blood 2022 #> 4044 114.9 6 1917 1917-06-02 02:00:01 bone 2022 #> 4045 119.8 7 1917 1917-07-02 12:00:00 blood 2023 #> 4046 119.8 7 1917 1917-07-02 12:00:00 bone 2023 #> 4047 154.5 8 1917 1917-08-01 22:00:01 blood 2024 #> 4048 154.5 8 1917 1917-08-01 22:00:01 bone 2024 #> 4049 129.4 9 1917 1917-09-01 08:00:01 blood 2025 #> 4050 129.4 9 1917 1917-09-01 08:00:01 bone 2025 #> 4051 72.2 10 1917 1917-10-01 18:00:00 blood 2026 #> 4052 72.2 10 1917 1917-10-01 18:00:00 bone 2026 #> 4053 96.4 11 1917 1917-11-01 04:00:01 blood 2027 #> 4054 96.4 11 1917 1917-11-01 04:00:01 bone 2027 #> 4055 129.3 12 1917 1917-12-01 14:00:01 blood 2028 #> 4056 129.3 12 1917 1917-12-01 14:00:01 bone 2028 #> 4057 96.0 1 1918 1918-01-01 00:00:00 blood 2029 #> 4058 96.0 1 1918 1918-01-01 00:00:00 bone 2029 #> 4059 65.3 2 1918 1918-01-31 10:00:01 blood 2030 #> 4060 65.3 2 1918 1918-01-31 10:00:01 bone 2030 #> 4061 72.2 3 1918 1918-03-02 20:00:01 blood 2031 #> 4062 72.2 3 1918 1918-03-02 20:00:01 bone 2031 #> 4063 80.5 4 1918 1918-04-02 06:00:00 blood 2032 #> 4064 80.5 4 1918 1918-04-02 06:00:00 bone 2032 #> 4065 76.7 5 1918 1918-05-02 16:00:01 blood 2033 #> 4066 76.7 5 1918 1918-05-02 16:00:01 bone 2033 #> 4067 59.4 6 1918 1918-06-02 02:00:01 blood 2034 #> 4068 59.4 6 1918 1918-06-02 02:00:01 bone 2034 #> 4069 107.6 7 1918 1918-07-02 12:00:00 blood 2035 #> 4070 107.6 7 1918 1918-07-02 12:00:00 bone 2035 #> 4071 101.7 8 1918 1918-08-01 22:00:01 blood 2036 #> 4072 101.7 8 1918 1918-08-01 22:00:01 bone 2036 #> 4073 79.9 9 1918 1918-09-01 08:00:01 blood 2037 #> 4074 79.9 9 1918 1918-09-01 08:00:01 bone 2037 #> 4075 85.0 10 1918 1918-10-01 18:00:00 blood 2038 #> 4076 85.0 10 1918 1918-10-01 18:00:00 bone 2038 #> 4077 83.4 11 1918 1918-11-01 04:00:01 blood 2039 #> 4078 83.4 11 1918 1918-11-01 04:00:01 bone 2039 #> 4079 59.2 12 1918 1918-12-01 14:00:01 blood 2040 #> 4080 59.2 12 1918 1918-12-01 14:00:01 bone 2040 #> 4081 48.1 1 1919 1919-01-01 00:00:00 blood 2041 #> 4082 48.1 1 1919 1919-01-01 00:00:00 bone 2041 #> 4083 79.5 2 1919 1919-01-31 10:00:01 blood 2042 #> 4084 79.5 2 1919 1919-01-31 10:00:01 bone 2042 #> 4085 66.5 3 1919 1919-03-02 20:00:01 blood 2043 #> 4086 66.5 3 1919 1919-03-02 20:00:01 bone 2043 #> 4087 51.8 4 1919 1919-04-02 06:00:00 blood 2044 #> 4088 51.8 4 1919 1919-04-02 06:00:00 bone 2044 #> 4089 88.1 5 1919 1919-05-02 16:00:01 blood 2045 #> 4090 88.1 5 1919 1919-05-02 16:00:01 bone 2045 #> 4091 111.2 6 1919 1919-06-02 02:00:01 blood 2046 #> 4092 111.2 6 1919 1919-06-02 02:00:01 bone 2046 #> 4093 64.7 7 1919 1919-07-02 12:00:00 blood 2047 #> 4094 64.7 7 1919 1919-07-02 12:00:00 bone 2047 #> 4095 69.0 8 1919 1919-08-01 22:00:01 blood 2048 #> 4096 69.0 8 1919 1919-08-01 22:00:01 bone 2048 #> 4097 54.7 9 1919 1919-09-01 08:00:01 blood 2049 #> 4098 54.7 9 1919 1919-09-01 08:00:01 bone 2049 #> 4099 52.8 10 1919 1919-10-01 18:00:00 blood 2050 #> 4100 52.8 10 1919 1919-10-01 18:00:00 bone 2050 #> 4101 42.0 11 1919 1919-11-01 04:00:01 blood 2051 #> 4102 42.0 11 1919 1919-11-01 04:00:01 bone 2051 #> 4103 34.9 12 1919 1919-12-01 14:00:01 blood 2052 #> 4104 34.9 12 1919 1919-12-01 14:00:01 bone 2052 #> 4105 51.1 1 1920 1920-01-01 00:00:00 blood 2053 #> 4106 51.1 1 1920 1920-01-01 00:00:00 bone 2053 #> 4107 53.9 2 1920 1920-01-31 12:00:01 blood 2054 #> 4108 53.9 2 1920 1920-01-31 12:00:01 bone 2054 #> 4109 70.2 3 1920 1920-03-02 00:00:01 blood 2055 #> 4110 70.2 3 1920 1920-03-02 00:00:01 bone 2055 #> 4111 14.8 4 1920 1920-04-01 12:00:00 blood 2056 #> 4112 14.8 4 1920 1920-04-01 12:00:00 bone 2056 #> 4113 33.3 5 1920 1920-05-02 00:00:01 blood 2057 #> 4114 33.3 5 1920 1920-05-02 00:00:01 bone 2057 #> 4115 38.7 6 1920 1920-06-01 12:00:01 blood 2058 #> 4116 38.7 6 1920 1920-06-01 12:00:01 bone 2058 #> 4117 27.5 7 1920 1920-07-02 00:00:00 blood 2059 #> 4118 27.5 7 1920 1920-07-02 00:00:00 bone 2059 #> 4119 19.2 8 1920 1920-08-01 12:00:01 blood 2060 #> 4120 19.2 8 1920 1920-08-01 12:00:01 bone 2060 #> 4121 36.3 9 1920 1920-09-01 00:00:01 blood 2061 #> 4122 36.3 9 1920 1920-09-01 00:00:01 bone 2061 #> 4123 49.6 10 1920 1920-10-01 12:00:00 blood 2062 #> 4124 49.6 10 1920 1920-10-01 12:00:00 bone 2062 #> 4125 27.2 11 1920 1920-11-01 00:00:01 blood 2063 #> 4126 27.2 11 1920 1920-11-01 00:00:01 bone 2063 #> 4127 29.9 12 1920 1920-12-01 12:00:01 blood 2064 #> 4128 29.9 12 1920 1920-12-01 12:00:01 bone 2064 #> 4129 31.5 1 1921 1921-01-01 00:00:00 blood 2065 #> 4130 31.5 1 1921 1921-01-01 00:00:00 bone 2065 #> 4131 28.3 2 1921 1921-01-31 10:00:01 blood 2066 #> 4132 28.3 2 1921 1921-01-31 10:00:01 bone 2066 #> 4133 26.7 3 1921 1921-03-02 20:00:01 blood 2067 #> 4134 26.7 3 1921 1921-03-02 20:00:01 bone 2067 #> 4135 32.4 4 1921 1921-04-02 06:00:00 blood 2068 #> 4136 32.4 4 1921 1921-04-02 06:00:00 bone 2068 #> 4137 22.2 5 1921 1921-05-02 16:00:01 blood 2069 #> 4138 22.2 5 1921 1921-05-02 16:00:01 bone 2069 #> 4139 33.7 6 1921 1921-06-02 02:00:01 blood 2070 #> 4140 33.7 6 1921 1921-06-02 02:00:01 bone 2070 #> 4141 41.9 7 1921 1921-07-02 12:00:00 blood 2071 #> 4142 41.9 7 1921 1921-07-02 12:00:00 bone 2071 #> 4143 22.8 8 1921 1921-08-01 22:00:01 blood 2072 #> 4144 22.8 8 1921 1921-08-01 22:00:01 bone 2072 #> 4145 17.8 9 1921 1921-09-01 08:00:01 blood 2073 #> 4146 17.8 9 1921 1921-09-01 08:00:01 bone 2073 #> 4147 18.2 10 1921 1921-10-01 18:00:00 blood 2074 #> 4148 18.2 10 1921 1921-10-01 18:00:00 bone 2074 #> 4149 17.8 11 1921 1921-11-01 04:00:01 blood 2075 #> 4150 17.8 11 1921 1921-11-01 04:00:01 bone 2075 #> 4151 20.3 12 1921 1921-12-01 14:00:01 blood 2076 #> 4152 20.3 12 1921 1921-12-01 14:00:01 bone 2076 #> 4153 11.8 1 1922 1922-01-01 00:00:00 blood 2077 #> 4154 11.8 1 1922 1922-01-01 00:00:00 bone 2077 #> 4155 26.4 2 1922 1922-01-31 10:00:01 blood 2078 #> 4156 26.4 2 1922 1922-01-31 10:00:01 bone 2078 #> 4157 54.7 3 1922 1922-03-02 20:00:01 blood 2079 #> 4158 54.7 3 1922 1922-03-02 20:00:01 bone 2079 #> 4159 11.0 4 1922 1922-04-02 06:00:00 blood 2080 #> 4160 11.0 4 1922 1922-04-02 06:00:00 bone 2080 #> 4161 8.0 5 1922 1922-05-02 16:00:01 blood 2081 #> 4162 8.0 5 1922 1922-05-02 16:00:01 bone 2081 #> 4163 5.8 6 1922 1922-06-02 02:00:01 blood 2082 #> 4164 5.8 6 1922 1922-06-02 02:00:01 bone 2082 #> 4165 10.9 7 1922 1922-07-02 12:00:00 blood 2083 #> 4166 10.9 7 1922 1922-07-02 12:00:00 bone 2083 #> 4167 6.5 8 1922 1922-08-01 22:00:01 blood 2084 #> 4168 6.5 8 1922 1922-08-01 22:00:01 bone 2084 #> 4169 4.7 9 1922 1922-09-01 08:00:01 blood 2085 #> 4170 4.7 9 1922 1922-09-01 08:00:01 bone 2085 #> 4171 6.2 10 1922 1922-10-01 18:00:00 blood 2086 #> 4172 6.2 10 1922 1922-10-01 18:00:00 bone 2086 #> 4173 7.4 11 1922 1922-11-01 04:00:01 blood 2087 #> 4174 7.4 11 1922 1922-11-01 04:00:01 bone 2087 #> 4175 17.5 12 1922 1922-12-01 14:00:01 blood 2088 #> 4176 17.5 12 1922 1922-12-01 14:00:01 bone 2088 #> 4177 4.5 1 1923 1923-01-01 00:00:00 blood 2089 #> 4178 4.5 1 1923 1923-01-01 00:00:00 bone 2089 #> 4179 1.5 2 1923 1923-01-31 10:00:01 blood 2090 #> 4180 1.5 2 1923 1923-01-31 10:00:01 bone 2090 #> 4181 3.3 3 1923 1923-03-02 20:00:01 blood 2091 #> 4182 3.3 3 1923 1923-03-02 20:00:01 bone 2091 #> 4183 6.1 4 1923 1923-04-02 06:00:00 blood 2092 #> 4184 6.1 4 1923 1923-04-02 06:00:00 bone 2092 #> 4185 3.2 5 1923 1923-05-02 16:00:01 blood 2093 #> 4186 3.2 5 1923 1923-05-02 16:00:01 bone 2093 #> 4187 9.1 6 1923 1923-06-02 02:00:01 blood 2094 #> 4188 9.1 6 1923 1923-06-02 02:00:01 bone 2094 #> 4189 3.5 7 1923 1923-07-02 12:00:00 blood 2095 #> 4190 3.5 7 1923 1923-07-02 12:00:00 bone 2095 #> 4191 0.5 8 1923 1923-08-01 22:00:01 blood 2096 #> 4192 0.5 8 1923 1923-08-01 22:00:01 bone 2096 #> 4193 13.2 9 1923 1923-09-01 08:00:01 blood 2097 #> 4194 13.2 9 1923 1923-09-01 08:00:01 bone 2097 #> 4195 11.6 10 1923 1923-10-01 18:00:00 blood 2098 #> 4196 11.6 10 1923 1923-10-01 18:00:00 bone 2098 #> 4197 10.0 11 1923 1923-11-01 04:00:01 blood 2099 #> 4198 10.0 11 1923 1923-11-01 04:00:01 bone 2099 #> 4199 2.8 12 1923 1923-12-01 14:00:01 blood 2100 #> 4200 2.8 12 1923 1923-12-01 14:00:01 bone 2100 #> 4201 0.5 1 1924 1924-01-01 00:00:00 blood 2101 #> 4202 0.5 1 1924 1924-01-01 00:00:00 bone 2101 #> 4203 5.1 2 1924 1924-01-31 12:00:01 blood 2102 #> 4204 5.1 2 1924 1924-01-31 12:00:01 bone 2102 #> 4205 1.8 3 1924 1924-03-02 00:00:01 blood 2103 #> 4206 1.8 3 1924 1924-03-02 00:00:01 bone 2103 #> 4207 11.3 4 1924 1924-04-01 12:00:00 blood 2104 #> 4208 11.3 4 1924 1924-04-01 12:00:00 bone 2104 #> 4209 20.8 5 1924 1924-05-02 00:00:01 blood 2105 #> 4210 20.8 5 1924 1924-05-02 00:00:01 bone 2105 #> 4211 24.0 6 1924 1924-06-01 12:00:01 blood 2106 #> 4212 24.0 6 1924 1924-06-01 12:00:01 bone 2106 #> 4213 28.1 7 1924 1924-07-02 00:00:00 blood 2107 #> 4214 28.1 7 1924 1924-07-02 00:00:00 bone 2107 #> 4215 19.3 8 1924 1924-08-01 12:00:01 blood 2108 #> 4216 19.3 8 1924 1924-08-01 12:00:01 bone 2108 #> 4217 25.1 9 1924 1924-09-01 00:00:01 blood 2109 #> 4218 25.1 9 1924 1924-09-01 00:00:01 bone 2109 #> 4219 25.6 10 1924 1924-10-01 12:00:00 blood 2110 #> 4220 25.6 10 1924 1924-10-01 12:00:00 bone 2110 #> 4221 22.5 11 1924 1924-11-01 00:00:01 blood 2111 #> 4222 22.5 11 1924 1924-11-01 00:00:01 bone 2111 #> 4223 16.5 12 1924 1924-12-01 12:00:01 blood 2112 #> 4224 16.5 12 1924 1924-12-01 12:00:01 bone 2112 #> 4225 5.5 1 1925 1925-01-01 00:00:00 blood 2113 #> 4226 5.5 1 1925 1925-01-01 00:00:00 bone 2113 #> 4227 23.2 2 1925 1925-01-31 10:00:01 blood 2114 #> 4228 23.2 2 1925 1925-01-31 10:00:01 bone 2114 #> 4229 18.0 3 1925 1925-03-02 20:00:01 blood 2115 #> 4230 18.0 3 1925 1925-03-02 20:00:01 bone 2115 #> 4231 31.7 4 1925 1925-04-02 06:00:00 blood 2116 #> 4232 31.7 4 1925 1925-04-02 06:00:00 bone 2116 #> 4233 42.8 5 1925 1925-05-02 16:00:01 blood 2117 #> 4234 42.8 5 1925 1925-05-02 16:00:01 bone 2117 #> 4235 47.5 6 1925 1925-06-02 02:00:01 blood 2118 #> 4236 47.5 6 1925 1925-06-02 02:00:01 bone 2118 #> 4237 38.5 7 1925 1925-07-02 12:00:00 blood 2119 #> 4238 38.5 7 1925 1925-07-02 12:00:00 bone 2119 #> 4239 37.9 8 1925 1925-08-01 22:00:01 blood 2120 #> 4240 37.9 8 1925 1925-08-01 22:00:01 bone 2120 #> 4241 60.2 9 1925 1925-09-01 08:00:01 blood 2121 #> 4242 60.2 9 1925 1925-09-01 08:00:01 bone 2121 #> 4243 69.2 10 1925 1925-10-01 18:00:00 blood 2122 #> 4244 69.2 10 1925 1925-10-01 18:00:00 bone 2122 #> 4245 58.6 11 1925 1925-11-01 04:00:01 blood 2123 #> 4246 58.6 11 1925 1925-11-01 04:00:01 bone 2123 #> 4247 98.6 12 1925 1925-12-01 14:00:01 blood 2124 #> 4248 98.6 12 1925 1925-12-01 14:00:01 bone 2124 #> 4249 71.8 1 1926 1926-01-01 00:00:00 blood 2125 #> 4250 71.8 1 1926 1926-01-01 00:00:00 bone 2125 #> 4251 70.0 2 1926 1926-01-31 10:00:01 blood 2126 #> 4252 70.0 2 1926 1926-01-31 10:00:01 bone 2126 #> 4253 62.5 3 1926 1926-03-02 20:00:01 blood 2127 #> 4254 62.5 3 1926 1926-03-02 20:00:01 bone 2127 #> 4255 38.5 4 1926 1926-04-02 06:00:00 blood 2128 #> 4256 38.5 4 1926 1926-04-02 06:00:00 bone 2128 #> 4257 64.3 5 1926 1926-05-02 16:00:01 blood 2129 #> 4258 64.3 5 1926 1926-05-02 16:00:01 bone 2129 #> 4259 73.5 6 1926 1926-06-02 02:00:01 blood 2130 #> 4260 73.5 6 1926 1926-06-02 02:00:01 bone 2130 #> 4261 52.3 7 1926 1926-07-02 12:00:00 blood 2131 #> 4262 52.3 7 1926 1926-07-02 12:00:00 bone 2131 #> 4263 61.6 8 1926 1926-08-01 22:00:01 blood 2132 #> 4264 61.6 8 1926 1926-08-01 22:00:01 bone 2132 #> 4265 60.8 9 1926 1926-09-01 08:00:01 blood 2133 #> 4266 60.8 9 1926 1926-09-01 08:00:01 bone 2133 #> 4267 71.5 10 1926 1926-10-01 18:00:00 blood 2134 #> 4268 71.5 10 1926 1926-10-01 18:00:00 bone 2134 #> 4269 60.5 11 1926 1926-11-01 04:00:01 blood 2135 #> 4270 60.5 11 1926 1926-11-01 04:00:01 bone 2135 #> 4271 79.4 12 1926 1926-12-01 14:00:01 blood 2136 #> 4272 79.4 12 1926 1926-12-01 14:00:01 bone 2136 #> 4273 81.6 1 1927 1927-01-01 00:00:00 blood 2137 #> 4274 81.6 1 1927 1927-01-01 00:00:00 bone 2137 #> 4275 93.0 2 1927 1927-01-31 10:00:01 blood 2138 #> 4276 93.0 2 1927 1927-01-31 10:00:01 bone 2138 #> 4277 69.6 3 1927 1927-03-02 20:00:01 blood 2139 #> 4278 69.6 3 1927 1927-03-02 20:00:01 bone 2139 #> 4279 93.5 4 1927 1927-04-02 06:00:00 blood 2140 #> 4280 93.5 4 1927 1927-04-02 06:00:00 bone 2140 #> 4281 79.1 5 1927 1927-05-02 16:00:01 blood 2141 #> 4282 79.1 5 1927 1927-05-02 16:00:01 bone 2141 #> 4283 59.1 6 1927 1927-06-02 02:00:01 blood 2142 #> 4284 59.1 6 1927 1927-06-02 02:00:01 bone 2142 #> 4285 54.9 7 1927 1927-07-02 12:00:00 blood 2143 #> 4286 54.9 7 1927 1927-07-02 12:00:00 bone 2143 #> 4287 53.8 8 1927 1927-08-01 22:00:01 blood 2144 #> 4288 53.8 8 1927 1927-08-01 22:00:01 bone 2144 #> 4289 68.4 9 1927 1927-09-01 08:00:01 blood 2145 #> 4290 68.4 9 1927 1927-09-01 08:00:01 bone 2145 #> 4291 63.1 10 1927 1927-10-01 18:00:00 blood 2146 #> 4292 63.1 10 1927 1927-10-01 18:00:00 bone 2146 #> 4293 67.2 11 1927 1927-11-01 04:00:01 blood 2147 #> 4294 67.2 11 1927 1927-11-01 04:00:01 bone 2147 #> 4295 45.2 12 1927 1927-12-01 14:00:01 blood 2148 #> 4296 45.2 12 1927 1927-12-01 14:00:01 bone 2148 #> 4297 83.5 1 1928 1928-01-01 00:00:00 blood 2149 #> 4298 83.5 1 1928 1928-01-01 00:00:00 bone 2149 #> 4299 73.5 2 1928 1928-01-31 12:00:01 blood 2150 #> 4300 73.5 2 1928 1928-01-31 12:00:01 bone 2150 #> 4301 85.4 3 1928 1928-03-02 00:00:01 blood 2151 #> 4302 85.4 3 1928 1928-03-02 00:00:01 bone 2151 #> 4303 80.6 4 1928 1928-04-01 12:00:00 blood 2152 #> 4304 80.6 4 1928 1928-04-01 12:00:00 bone 2152 #> 4305 76.9 5 1928 1928-05-02 00:00:01 blood 2153 #> 4306 76.9 5 1928 1928-05-02 00:00:01 bone 2153 #> 4307 91.4 6 1928 1928-06-01 12:00:01 blood 2154 #> 4308 91.4 6 1928 1928-06-01 12:00:01 bone 2154 #> 4309 98.0 7 1928 1928-07-02 00:00:00 blood 2155 #> 4310 98.0 7 1928 1928-07-02 00:00:00 bone 2155 #> 4311 83.8 8 1928 1928-08-01 12:00:01 blood 2156 #> 4312 83.8 8 1928 1928-08-01 12:00:01 bone 2156 #> 4313 89.7 9 1928 1928-09-01 00:00:01 blood 2157 #> 4314 89.7 9 1928 1928-09-01 00:00:01 bone 2157 #> 4315 61.4 10 1928 1928-10-01 12:00:00 blood 2158 #> 4316 61.4 10 1928 1928-10-01 12:00:00 bone 2158 #> 4317 50.3 11 1928 1928-11-01 00:00:01 blood 2159 #> 4318 50.3 11 1928 1928-11-01 00:00:01 bone 2159 #> 4319 59.0 12 1928 1928-12-01 12:00:01 blood 2160 #> 4320 59.0 12 1928 1928-12-01 12:00:01 bone 2160 #> 4321 68.9 1 1929 1929-01-01 00:00:00 blood 2161 #> 4322 68.9 1 1929 1929-01-01 00:00:00 bone 2161 #> 4323 64.1 2 1929 1929-01-31 10:00:01 blood 2162 #> 4324 64.1 2 1929 1929-01-31 10:00:01 bone 2162 #> 4325 50.2 3 1929 1929-03-02 20:00:01 blood 2163 #> 4326 50.2 3 1929 1929-03-02 20:00:01 bone 2163 #> 4327 52.8 4 1929 1929-04-02 06:00:00 blood 2164 #> 4328 52.8 4 1929 1929-04-02 06:00:00 bone 2164 #> 4329 58.2 5 1929 1929-05-02 16:00:01 blood 2165 #> 4330 58.2 5 1929 1929-05-02 16:00:01 bone 2165 #> 4331 71.9 6 1929 1929-06-02 02:00:01 blood 2166 #> 4332 71.9 6 1929 1929-06-02 02:00:01 bone 2166 #> 4333 70.2 7 1929 1929-07-02 12:00:00 blood 2167 #> 4334 70.2 7 1929 1929-07-02 12:00:00 bone 2167 #> 4335 65.8 8 1929 1929-08-01 22:00:01 blood 2168 #> 4336 65.8 8 1929 1929-08-01 22:00:01 bone 2168 #> 4337 34.4 9 1929 1929-09-01 08:00:01 blood 2169 #> 4338 34.4 9 1929 1929-09-01 08:00:01 bone 2169 #> 4339 54.0 10 1929 1929-10-01 18:00:00 blood 2170 #> 4340 54.0 10 1929 1929-10-01 18:00:00 bone 2170 #> 4341 81.1 11 1929 1929-11-01 04:00:01 blood 2171 #> 4342 81.1 11 1929 1929-11-01 04:00:01 bone 2171 #> 4343 108.0 12 1929 1929-12-01 14:00:01 blood 2172 #> 4344 108.0 12 1929 1929-12-01 14:00:01 bone 2172 #> 4345 65.3 1 1930 1930-01-01 00:00:00 blood 2173 #> 4346 65.3 1 1930 1930-01-01 00:00:00 bone 2173 #> 4347 49.2 2 1930 1930-01-31 10:00:01 blood 2174 #> 4348 49.2 2 1930 1930-01-31 10:00:01 bone 2174 #> 4349 35.0 3 1930 1930-03-02 20:00:01 blood 2175 #> 4350 35.0 3 1930 1930-03-02 20:00:01 bone 2175 #> 4351 38.2 4 1930 1930-04-02 06:00:00 blood 2176 #> 4352 38.2 4 1930 1930-04-02 06:00:00 bone 2176 #> 4353 36.8 5 1930 1930-05-02 16:00:01 blood 2177 #> 4354 36.8 5 1930 1930-05-02 16:00:01 bone 2177 #> 4355 28.8 6 1930 1930-06-02 02:00:01 blood 2178 #> 4356 28.8 6 1930 1930-06-02 02:00:01 bone 2178 #> 4357 21.9 7 1930 1930-07-02 12:00:00 blood 2179 #> 4358 21.9 7 1930 1930-07-02 12:00:00 bone 2179 #> 4359 24.9 8 1930 1930-08-01 22:00:01 blood 2180 #> 4360 24.9 8 1930 1930-08-01 22:00:01 bone 2180 #> 4361 32.1 9 1930 1930-09-01 08:00:01 blood 2181 #> 4362 32.1 9 1930 1930-09-01 08:00:01 bone 2181 #> 4363 34.4 10 1930 1930-10-01 18:00:00 blood 2182 #> 4364 34.4 10 1930 1930-10-01 18:00:00 bone 2182 #> 4365 35.6 11 1930 1930-11-01 04:00:01 blood 2183 #> 4366 35.6 11 1930 1930-11-01 04:00:01 bone 2183 #> 4367 25.8 12 1930 1930-12-01 14:00:01 blood 2184 #> 4368 25.8 12 1930 1930-12-01 14:00:01 bone 2184 #> 4369 14.6 1 1931 1931-01-01 00:00:00 blood 2185 #> 4370 14.6 1 1931 1931-01-01 00:00:00 bone 2185 #> 4371 43.1 2 1931 1931-01-31 10:00:01 blood 2186 #> 4372 43.1 2 1931 1931-01-31 10:00:01 bone 2186 #> 4373 30.0 3 1931 1931-03-02 20:00:01 blood 2187 #> 4374 30.0 3 1931 1931-03-02 20:00:01 bone 2187 #> 4375 31.2 4 1931 1931-04-02 06:00:00 blood 2188 #> 4376 31.2 4 1931 1931-04-02 06:00:00 bone 2188 #> 4377 24.6 5 1931 1931-05-02 16:00:01 blood 2189 #> 4378 24.6 5 1931 1931-05-02 16:00:01 bone 2189 #> 4379 15.3 6 1931 1931-06-02 02:00:01 blood 2190 #> 4380 15.3 6 1931 1931-06-02 02:00:01 bone 2190 #> 4381 17.4 7 1931 1931-07-02 12:00:00 blood 2191 #> 4382 17.4 7 1931 1931-07-02 12:00:00 bone 2191 #> 4383 13.0 8 1931 1931-08-01 22:00:01 blood 2192 #> 4384 13.0 8 1931 1931-08-01 22:00:01 bone 2192 #> 4385 19.0 9 1931 1931-09-01 08:00:01 blood 2193 #> 4386 19.0 9 1931 1931-09-01 08:00:01 bone 2193 #> 4387 10.0 10 1931 1931-10-01 18:00:00 blood 2194 #> 4388 10.0 10 1931 1931-10-01 18:00:00 bone 2194 #> 4389 18.7 11 1931 1931-11-01 04:00:01 blood 2195 #> 4390 18.7 11 1931 1931-11-01 04:00:01 bone 2195 #> 4391 17.8 12 1931 1931-12-01 14:00:01 blood 2196 #> 4392 17.8 12 1931 1931-12-01 14:00:01 bone 2196 #> 4393 12.1 1 1932 1932-01-01 00:00:00 blood 2197 #> 4394 12.1 1 1932 1932-01-01 00:00:00 bone 2197 #> 4395 10.6 2 1932 1932-01-31 12:00:01 blood 2198 #> 4396 10.6 2 1932 1932-01-31 12:00:01 bone 2198 #> 4397 11.2 3 1932 1932-03-02 00:00:01 blood 2199 #> 4398 11.2 3 1932 1932-03-02 00:00:01 bone 2199 #> 4399 11.2 4 1932 1932-04-01 12:00:00 blood 2200 #> 4400 11.2 4 1932 1932-04-01 12:00:00 bone 2200 #> 4401 17.9 5 1932 1932-05-02 00:00:01 blood 2201 #> 4402 17.9 5 1932 1932-05-02 00:00:01 bone 2201 #> 4403 22.2 6 1932 1932-06-01 12:00:01 blood 2202 #> 4404 22.2 6 1932 1932-06-01 12:00:01 bone 2202 #> 4405 9.6 7 1932 1932-07-02 00:00:00 blood 2203 #> 4406 9.6 7 1932 1932-07-02 00:00:00 bone 2203 #> 4407 6.8 8 1932 1932-08-01 12:00:01 blood 2204 #> 4408 6.8 8 1932 1932-08-01 12:00:01 bone 2204 #> 4409 4.0 9 1932 1932-09-01 00:00:01 blood 2205 #> 4410 4.0 9 1932 1932-09-01 00:00:01 bone 2205 #> 4411 8.9 10 1932 1932-10-01 12:00:00 blood 2206 #> 4412 8.9 10 1932 1932-10-01 12:00:00 bone 2206 #> 4413 8.2 11 1932 1932-11-01 00:00:01 blood 2207 #> 4414 8.2 11 1932 1932-11-01 00:00:01 bone 2207 #> 4415 11.0 12 1932 1932-12-01 12:00:01 blood 2208 #> 4416 11.0 12 1932 1932-12-01 12:00:01 bone 2208 #> 4417 12.3 1 1933 1933-01-01 00:00:00 blood 2209 #> 4418 12.3 1 1933 1933-01-01 00:00:00 bone 2209 #> 4419 22.2 2 1933 1933-01-31 10:00:01 blood 2210 #> 4420 22.2 2 1933 1933-01-31 10:00:01 bone 2210 #> 4421 10.1 3 1933 1933-03-02 20:00:01 blood 2211 #> 4422 10.1 3 1933 1933-03-02 20:00:01 bone 2211 #> 4423 2.9 4 1933 1933-04-02 06:00:00 blood 2212 #> 4424 2.9 4 1933 1933-04-02 06:00:00 bone 2212 #> 4425 3.2 5 1933 1933-05-02 16:00:01 blood 2213 #> 4426 3.2 5 1933 1933-05-02 16:00:01 bone 2213 #> 4427 5.2 6 1933 1933-06-02 02:00:01 blood 2214 #> 4428 5.2 6 1933 1933-06-02 02:00:01 bone 2214 #> 4429 2.8 7 1933 1933-07-02 12:00:00 blood 2215 #> 4430 2.8 7 1933 1933-07-02 12:00:00 bone 2215 #> 4431 0.2 8 1933 1933-08-01 22:00:01 blood 2216 #> 4432 0.2 8 1933 1933-08-01 22:00:01 bone 2216 #> 4433 5.1 9 1933 1933-09-01 08:00:01 blood 2217 #> 4434 5.1 9 1933 1933-09-01 08:00:01 bone 2217 #> 4435 3.0 10 1933 1933-10-01 18:00:00 blood 2218 #> 4436 3.0 10 1933 1933-10-01 18:00:00 bone 2218 #> 4437 0.6 11 1933 1933-11-01 04:00:01 blood 2219 #> 4438 0.6 11 1933 1933-11-01 04:00:01 bone 2219 #> 4439 0.3 12 1933 1933-12-01 14:00:01 blood 2220 #> 4440 0.3 12 1933 1933-12-01 14:00:01 bone 2220 #> 4441 3.4 1 1934 1934-01-01 00:00:00 blood 2221 #> 4442 3.4 1 1934 1934-01-01 00:00:00 bone 2221 #> 4443 7.8 2 1934 1934-01-31 10:00:01 blood 2222 #> 4444 7.8 2 1934 1934-01-31 10:00:01 bone 2222 #> 4445 4.3 3 1934 1934-03-02 20:00:01 blood 2223 #> 4446 4.3 3 1934 1934-03-02 20:00:01 bone 2223 #> 4447 11.3 4 1934 1934-04-02 06:00:00 blood 2224 #> 4448 11.3 4 1934 1934-04-02 06:00:00 bone 2224 #> 4449 19.7 5 1934 1934-05-02 16:00:01 blood 2225 #> 4450 19.7 5 1934 1934-05-02 16:00:01 bone 2225 #> 4451 6.7 6 1934 1934-06-02 02:00:01 blood 2226 #> 4452 6.7 6 1934 1934-06-02 02:00:01 bone 2226 #> 4453 9.3 7 1934 1934-07-02 12:00:00 blood 2227 #> 4454 9.3 7 1934 1934-07-02 12:00:00 bone 2227 #> 4455 8.3 8 1934 1934-08-01 22:00:01 blood 2228 #> 4456 8.3 8 1934 1934-08-01 22:00:01 bone 2228 #> 4457 4.0 9 1934 1934-09-01 08:00:01 blood 2229 #> 4458 4.0 9 1934 1934-09-01 08:00:01 bone 2229 #> 4459 5.7 10 1934 1934-10-01 18:00:00 blood 2230 #> 4460 5.7 10 1934 1934-10-01 18:00:00 bone 2230 #> 4461 8.7 11 1934 1934-11-01 04:00:01 blood 2231 #> 4462 8.7 11 1934 1934-11-01 04:00:01 bone 2231 #> 4463 15.4 12 1934 1934-12-01 14:00:01 blood 2232 #> 4464 15.4 12 1934 1934-12-01 14:00:01 bone 2232 #> 4465 18.9 1 1935 1935-01-01 00:00:00 blood 2233 #> 4466 18.9 1 1935 1935-01-01 00:00:00 bone 2233 #> 4467 20.5 2 1935 1935-01-31 10:00:01 blood 2234 #> 4468 20.5 2 1935 1935-01-31 10:00:01 bone 2234 #> 4469 23.1 3 1935 1935-03-02 20:00:01 blood 2235 #> 4470 23.1 3 1935 1935-03-02 20:00:01 bone 2235 #> 4471 12.2 4 1935 1935-04-02 06:00:00 blood 2236 #> 4472 12.2 4 1935 1935-04-02 06:00:00 bone 2236 #> 4473 27.3 5 1935 1935-05-02 16:00:01 blood 2237 #> 4474 27.3 5 1935 1935-05-02 16:00:01 bone 2237 #> 4475 45.7 6 1935 1935-06-02 02:00:01 blood 2238 #> 4476 45.7 6 1935 1935-06-02 02:00:01 bone 2238 #> 4477 33.9 7 1935 1935-07-02 12:00:00 blood 2239 #> 4478 33.9 7 1935 1935-07-02 12:00:00 bone 2239 #> 4479 30.1 8 1935 1935-08-01 22:00:01 blood 2240 #> 4480 30.1 8 1935 1935-08-01 22:00:01 bone 2240 #> 4481 42.1 9 1935 1935-09-01 08:00:01 blood 2241 #> 4482 42.1 9 1935 1935-09-01 08:00:01 bone 2241 #> 4483 53.2 10 1935 1935-10-01 18:00:00 blood 2242 #> 4484 53.2 10 1935 1935-10-01 18:00:00 bone 2242 #> 4485 64.2 11 1935 1935-11-01 04:00:01 blood 2243 #> 4486 64.2 11 1935 1935-11-01 04:00:01 bone 2243 #> 4487 61.5 12 1935 1935-12-01 14:00:01 blood 2244 #> 4488 61.5 12 1935 1935-12-01 14:00:01 bone 2244 #> 4489 62.8 1 1936 1936-01-01 00:00:00 blood 2245 #> 4490 62.8 1 1936 1936-01-01 00:00:00 bone 2245 #> 4491 74.3 2 1936 1936-01-31 12:00:01 blood 2246 #> 4492 74.3 2 1936 1936-01-31 12:00:01 bone 2246 #> 4493 77.1 3 1936 1936-03-02 00:00:01 blood 2247 #> 4494 77.1 3 1936 1936-03-02 00:00:01 bone 2247 #> 4495 74.9 4 1936 1936-04-01 12:00:00 blood 2248 #> 4496 74.9 4 1936 1936-04-01 12:00:00 bone 2248 #> 4497 54.6 5 1936 1936-05-02 00:00:01 blood 2249 #> 4498 54.6 5 1936 1936-05-02 00:00:01 bone 2249 #> 4499 70.0 6 1936 1936-06-01 12:00:01 blood 2250 #> 4500 70.0 6 1936 1936-06-01 12:00:01 bone 2250 #> 4501 52.3 7 1936 1936-07-02 00:00:00 blood 2251 #> 4502 52.3 7 1936 1936-07-02 00:00:00 bone 2251 #> 4503 87.0 8 1936 1936-08-01 12:00:01 blood 2252 #> 4504 87.0 8 1936 1936-08-01 12:00:01 bone 2252 #> 4505 76.0 9 1936 1936-09-01 00:00:01 blood 2253 #> 4506 76.0 9 1936 1936-09-01 00:00:01 bone 2253 #> 4507 89.0 10 1936 1936-10-01 12:00:00 blood 2254 #> 4508 89.0 10 1936 1936-10-01 12:00:00 bone 2254 #> 4509 115.4 11 1936 1936-11-01 00:00:01 blood 2255 #> 4510 115.4 11 1936 1936-11-01 00:00:01 bone 2255 #> 4511 123.4 12 1936 1936-12-01 12:00:01 blood 2256 #> 4512 123.4 12 1936 1936-12-01 12:00:01 bone 2256 #> 4513 132.5 1 1937 1937-01-01 00:00:00 blood 2257 #> 4514 132.5 1 1937 1937-01-01 00:00:00 bone 2257 #> 4515 128.5 2 1937 1937-01-31 10:00:01 blood 2258 #> 4516 128.5 2 1937 1937-01-31 10:00:01 bone 2258 #> 4517 83.9 3 1937 1937-03-02 20:00:01 blood 2259 #> 4518 83.9 3 1937 1937-03-02 20:00:01 bone 2259 #> 4519 109.3 4 1937 1937-04-02 06:00:00 blood 2260 #> 4520 109.3 4 1937 1937-04-02 06:00:00 bone 2260 #> 4521 116.7 5 1937 1937-05-02 16:00:01 blood 2261 #> 4522 116.7 5 1937 1937-05-02 16:00:01 bone 2261 #> 4523 130.3 6 1937 1937-06-02 02:00:01 blood 2262 #> 4524 130.3 6 1937 1937-06-02 02:00:01 bone 2262 #> 4525 145.1 7 1937 1937-07-02 12:00:00 blood 2263 #> 4526 145.1 7 1937 1937-07-02 12:00:00 bone 2263 #> 4527 137.7 8 1937 1937-08-01 22:00:01 blood 2264 #> 4528 137.7 8 1937 1937-08-01 22:00:01 bone 2264 #> 4529 100.7 9 1937 1937-09-01 08:00:01 blood 2265 #> 4530 100.7 9 1937 1937-09-01 08:00:01 bone 2265 #> 4531 124.9 10 1937 1937-10-01 18:00:00 blood 2266 #> 4532 124.9 10 1937 1937-10-01 18:00:00 bone 2266 #> 4533 74.4 11 1937 1937-11-01 04:00:01 blood 2267 #> 4534 74.4 11 1937 1937-11-01 04:00:01 bone 2267 #> 4535 88.8 12 1937 1937-12-01 14:00:01 blood 2268 #> 4536 88.8 12 1937 1937-12-01 14:00:01 bone 2268 #> 4537 98.4 1 1938 1938-01-01 00:00:00 blood 2269 #> 4538 98.4 1 1938 1938-01-01 00:00:00 bone 2269 #> 4539 119.2 2 1938 1938-01-31 10:00:01 blood 2270 #> 4540 119.2 2 1938 1938-01-31 10:00:01 bone 2270 #> 4541 86.5 3 1938 1938-03-02 20:00:01 blood 2271 #> 4542 86.5 3 1938 1938-03-02 20:00:01 bone 2271 #> 4543 101.0 4 1938 1938-04-02 06:00:00 blood 2272 #> 4544 101.0 4 1938 1938-04-02 06:00:00 bone 2272 #> 4545 127.4 5 1938 1938-05-02 16:00:01 blood 2273 #> 4546 127.4 5 1938 1938-05-02 16:00:01 bone 2273 #> 4547 97.5 6 1938 1938-06-02 02:00:01 blood 2274 #> 4548 97.5 6 1938 1938-06-02 02:00:01 bone 2274 #> 4549 165.3 7 1938 1938-07-02 12:00:00 blood 2275 #> 4550 165.3 7 1938 1938-07-02 12:00:00 bone 2275 #> 4551 115.7 8 1938 1938-08-01 22:00:01 blood 2276 #> 4552 115.7 8 1938 1938-08-01 22:00:01 bone 2276 #> 4553 89.6 9 1938 1938-09-01 08:00:01 blood 2277 #> 4554 89.6 9 1938 1938-09-01 08:00:01 bone 2277 #> 4555 99.1 10 1938 1938-10-01 18:00:00 blood 2278 #> 4556 99.1 10 1938 1938-10-01 18:00:00 bone 2278 #> 4557 122.2 11 1938 1938-11-01 04:00:01 blood 2279 #> 4558 122.2 11 1938 1938-11-01 04:00:01 bone 2279 #> 4559 92.7 12 1938 1938-12-01 14:00:01 blood 2280 #> 4560 92.7 12 1938 1938-12-01 14:00:01 bone 2280 #> 4561 80.3 1 1939 1939-01-01 00:00:00 blood 2281 #> 4562 80.3 1 1939 1939-01-01 00:00:00 bone 2281 #> 4563 77.4 2 1939 1939-01-31 10:00:01 blood 2282 #> 4564 77.4 2 1939 1939-01-31 10:00:01 bone 2282 #> 4565 64.6 3 1939 1939-03-02 20:00:01 blood 2283 #> 4566 64.6 3 1939 1939-03-02 20:00:01 bone 2283 #> 4567 109.1 4 1939 1939-04-02 06:00:00 blood 2284 #> 4568 109.1 4 1939 1939-04-02 06:00:00 bone 2284 #> 4569 118.3 5 1939 1939-05-02 16:00:01 blood 2285 #> 4570 118.3 5 1939 1939-05-02 16:00:01 bone 2285 #> 4571 101.0 6 1939 1939-06-02 02:00:01 blood 2286 #> 4572 101.0 6 1939 1939-06-02 02:00:01 bone 2286 #> 4573 97.6 7 1939 1939-07-02 12:00:00 blood 2287 #> 4574 97.6 7 1939 1939-07-02 12:00:00 bone 2287 #> 4575 105.8 8 1939 1939-08-01 22:00:01 blood 2288 #> 4576 105.8 8 1939 1939-08-01 22:00:01 bone 2288 #> 4577 112.6 9 1939 1939-09-01 08:00:01 blood 2289 #> 4578 112.6 9 1939 1939-09-01 08:00:01 bone 2289 #> 4579 88.1 10 1939 1939-10-01 18:00:00 blood 2290 #> 4580 88.1 10 1939 1939-10-01 18:00:00 bone 2290 #> 4581 68.1 11 1939 1939-11-01 04:00:01 blood 2291 #> 4582 68.1 11 1939 1939-11-01 04:00:01 bone 2291 #> 4583 42.1 12 1939 1939-12-01 14:00:01 blood 2292 #> 4584 42.1 12 1939 1939-12-01 14:00:01 bone 2292 #> 4585 50.5 1 1940 1940-01-01 00:00:00 blood 2293 #> 4586 50.5 1 1940 1940-01-01 00:00:00 bone 2293 #> 4587 59.4 2 1940 1940-01-31 12:00:01 blood 2294 #> 4588 59.4 2 1940 1940-01-31 12:00:01 bone 2294 #> 4589 83.3 3 1940 1940-03-02 00:00:01 blood 2295 #> 4590 83.3 3 1940 1940-03-02 00:00:01 bone 2295 #> 4591 60.7 4 1940 1940-04-01 12:00:00 blood 2296 #> 4592 60.7 4 1940 1940-04-01 12:00:00 bone 2296 #> 4593 54.4 5 1940 1940-05-02 00:00:01 blood 2297 #> 4594 54.4 5 1940 1940-05-02 00:00:01 bone 2297 #> 4595 83.9 6 1940 1940-06-01 12:00:01 blood 2298 #> 4596 83.9 6 1940 1940-06-01 12:00:01 bone 2298 #> 4597 67.5 7 1940 1940-07-02 00:00:00 blood 2299 #> 4598 67.5 7 1940 1940-07-02 00:00:00 bone 2299 #> 4599 105.5 8 1940 1940-08-01 12:00:01 blood 2300 #> 4600 105.5 8 1940 1940-08-01 12:00:01 bone 2300 #> 4601 66.5 9 1940 1940-09-01 00:00:01 blood 2301 #> 4602 66.5 9 1940 1940-09-01 00:00:01 bone 2301 #> 4603 55.0 10 1940 1940-10-01 12:00:00 blood 2302 #> 4604 55.0 10 1940 1940-10-01 12:00:00 bone 2302 #> 4605 58.4 11 1940 1940-11-01 00:00:01 blood 2303 #> 4606 58.4 11 1940 1940-11-01 00:00:01 bone 2303 #> 4607 68.3 12 1940 1940-12-01 12:00:01 blood 2304 #> 4608 68.3 12 1940 1940-12-01 12:00:01 bone 2304 #> 4609 45.6 1 1941 1941-01-01 00:00:00 blood 2305 #> 4610 45.6 1 1941 1941-01-01 00:00:00 bone 2305 #> 4611 44.5 2 1941 1941-01-31 10:00:01 blood 2306 #> 4612 44.5 2 1941 1941-01-31 10:00:01 bone 2306 #> 4613 46.4 3 1941 1941-03-02 20:00:01 blood 2307 #> 4614 46.4 3 1941 1941-03-02 20:00:01 bone 2307 #> 4615 32.8 4 1941 1941-04-02 06:00:00 blood 2308 #> 4616 32.8 4 1941 1941-04-02 06:00:00 bone 2308 #> 4617 29.5 5 1941 1941-05-02 16:00:01 blood 2309 #> 4618 29.5 5 1941 1941-05-02 16:00:01 bone 2309 #> 4619 59.8 6 1941 1941-06-02 02:00:01 blood 2310 #> 4620 59.8 6 1941 1941-06-02 02:00:01 bone 2310 #> 4621 66.9 7 1941 1941-07-02 12:00:00 blood 2311 #> 4622 66.9 7 1941 1941-07-02 12:00:00 bone 2311 #> 4623 60.0 8 1941 1941-08-01 22:00:01 blood 2312 #> 4624 60.0 8 1941 1941-08-01 22:00:01 bone 2312 #> 4625 65.9 9 1941 1941-09-01 08:00:01 blood 2313 #> 4626 65.9 9 1941 1941-09-01 08:00:01 bone 2313 #> 4627 46.3 10 1941 1941-10-01 18:00:00 blood 2314 #> 4628 46.3 10 1941 1941-10-01 18:00:00 bone 2314 #> 4629 38.3 11 1941 1941-11-01 04:00:01 blood 2315 #> 4630 38.3 11 1941 1941-11-01 04:00:01 bone 2315 #> 4631 33.7 12 1941 1941-12-01 14:00:01 blood 2316 #> 4632 33.7 12 1941 1941-12-01 14:00:01 bone 2316 #> 4633 35.6 1 1942 1942-01-01 00:00:00 blood 2317 #> 4634 35.6 1 1942 1942-01-01 00:00:00 bone 2317 #> 4635 52.8 2 1942 1942-01-31 10:00:01 blood 2318 #> 4636 52.8 2 1942 1942-01-31 10:00:01 bone 2318 #> 4637 54.2 3 1942 1942-03-02 20:00:01 blood 2319 #> 4638 54.2 3 1942 1942-03-02 20:00:01 bone 2319 #> 4639 60.7 4 1942 1942-04-02 06:00:00 blood 2320 #> 4640 60.7 4 1942 1942-04-02 06:00:00 bone 2320 #> 4641 25.0 5 1942 1942-05-02 16:00:01 blood 2321 #> 4642 25.0 5 1942 1942-05-02 16:00:01 bone 2321 #> 4643 11.4 6 1942 1942-06-02 02:00:01 blood 2322 #> 4644 11.4 6 1942 1942-06-02 02:00:01 bone 2322 #> 4645 17.7 7 1942 1942-07-02 12:00:00 blood 2323 #> 4646 17.7 7 1942 1942-07-02 12:00:00 bone 2323 #> 4647 20.2 8 1942 1942-08-01 22:00:01 blood 2324 #> 4648 20.2 8 1942 1942-08-01 22:00:01 bone 2324 #> 4649 17.2 9 1942 1942-09-01 08:00:01 blood 2325 #> 4650 17.2 9 1942 1942-09-01 08:00:01 bone 2325 #> 4651 19.2 10 1942 1942-10-01 18:00:00 blood 2326 #> 4652 19.2 10 1942 1942-10-01 18:00:00 bone 2326 #> 4653 30.7 11 1942 1942-11-01 04:00:01 blood 2327 #> 4654 30.7 11 1942 1942-11-01 04:00:01 bone 2327 #> 4655 22.5 12 1942 1942-12-01 14:00:01 blood 2328 #> 4656 22.5 12 1942 1942-12-01 14:00:01 bone 2328 #> 4657 12.4 1 1943 1943-01-01 00:00:00 blood 2329 #> 4658 12.4 1 1943 1943-01-01 00:00:00 bone 2329 #> 4659 28.9 2 1943 1943-01-31 10:00:01 blood 2330 #> 4660 28.9 2 1943 1943-01-31 10:00:01 bone 2330 #> 4661 27.4 3 1943 1943-03-02 20:00:01 blood 2331 #> 4662 27.4 3 1943 1943-03-02 20:00:01 bone 2331 #> 4663 26.1 4 1943 1943-04-02 06:00:00 blood 2332 #> 4664 26.1 4 1943 1943-04-02 06:00:00 bone 2332 #> 4665 14.1 5 1943 1943-05-02 16:00:01 blood 2333 #> 4666 14.1 5 1943 1943-05-02 16:00:01 bone 2333 #> 4667 7.6 6 1943 1943-06-02 02:00:01 blood 2334 #> 4668 7.6 6 1943 1943-06-02 02:00:01 bone 2334 #> 4669 13.2 7 1943 1943-07-02 12:00:00 blood 2335 #> 4670 13.2 7 1943 1943-07-02 12:00:00 bone 2335 #> 4671 19.4 8 1943 1943-08-01 22:00:01 blood 2336 #> 4672 19.4 8 1943 1943-08-01 22:00:01 bone 2336 #> 4673 10.0 9 1943 1943-09-01 08:00:01 blood 2337 #> 4674 10.0 9 1943 1943-09-01 08:00:01 bone 2337 #> 4675 7.8 10 1943 1943-10-01 18:00:00 blood 2338 #> 4676 7.8 10 1943 1943-10-01 18:00:00 bone 2338 #> 4677 10.2 11 1943 1943-11-01 04:00:01 blood 2339 #> 4678 10.2 11 1943 1943-11-01 04:00:01 bone 2339 #> 4679 18.8 12 1943 1943-12-01 14:00:01 blood 2340 #> 4680 18.8 12 1943 1943-12-01 14:00:01 bone 2340 #> 4681 3.7 1 1944 1944-01-01 00:00:00 blood 2341 #> 4682 3.7 1 1944 1944-01-01 00:00:00 bone 2341 #> 4683 0.5 2 1944 1944-01-31 12:00:01 blood 2342 #> 4684 0.5 2 1944 1944-01-31 12:00:01 bone 2342 #> 4685 11.0 3 1944 1944-03-02 00:00:01 blood 2343 #> 4686 11.0 3 1944 1944-03-02 00:00:01 bone 2343 #> 4687 0.3 4 1944 1944-04-01 12:00:00 blood 2344 #> 4688 0.3 4 1944 1944-04-01 12:00:00 bone 2344 #> 4689 2.5 5 1944 1944-05-02 00:00:01 blood 2345 #> 4690 2.5 5 1944 1944-05-02 00:00:01 bone 2345 #> 4691 5.0 6 1944 1944-06-01 12:00:01 blood 2346 #> 4692 5.0 6 1944 1944-06-01 12:00:01 bone 2346 #> 4693 5.0 7 1944 1944-07-02 00:00:00 blood 2347 #> 4694 5.0 7 1944 1944-07-02 00:00:00 bone 2347 #> 4695 16.7 8 1944 1944-08-01 12:00:01 blood 2348 #> 4696 16.7 8 1944 1944-08-01 12:00:01 bone 2348 #> 4697 14.3 9 1944 1944-09-01 00:00:01 blood 2349 #> 4698 14.3 9 1944 1944-09-01 00:00:01 bone 2349 #> 4699 16.9 10 1944 1944-10-01 12:00:00 blood 2350 #> 4700 16.9 10 1944 1944-10-01 12:00:00 bone 2350 #> 4701 10.8 11 1944 1944-11-01 00:00:01 blood 2351 #> 4702 10.8 11 1944 1944-11-01 00:00:01 bone 2351 #> 4703 28.4 12 1944 1944-12-01 12:00:01 blood 2352 #> 4704 28.4 12 1944 1944-12-01 12:00:01 bone 2352 #> 4705 18.5 1 1945 1945-01-01 00:00:00 blood 2353 #> 4706 18.5 1 1945 1945-01-01 00:00:00 bone 2353 #> 4707 12.7 2 1945 1945-01-31 10:00:01 blood 2354 #> 4708 12.7 2 1945 1945-01-31 10:00:01 bone 2354 #> 4709 21.5 3 1945 1945-03-02 20:00:01 blood 2355 #> 4710 21.5 3 1945 1945-03-02 20:00:01 bone 2355 #> 4711 32.0 4 1945 1945-04-02 06:00:00 blood 2356 #> 4712 32.0 4 1945 1945-04-02 06:00:00 bone 2356 #> 4713 30.6 5 1945 1945-05-02 16:00:01 blood 2357 #> 4714 30.6 5 1945 1945-05-02 16:00:01 bone 2357 #> 4715 36.2 6 1945 1945-06-02 02:00:01 blood 2358 #> 4716 36.2 6 1945 1945-06-02 02:00:01 bone 2358 #> 4717 42.6 7 1945 1945-07-02 12:00:00 blood 2359 #> 4718 42.6 7 1945 1945-07-02 12:00:00 bone 2359 #> 4719 25.9 8 1945 1945-08-01 22:00:01 blood 2360 #> 4720 25.9 8 1945 1945-08-01 22:00:01 bone 2360 #> 4721 34.9 9 1945 1945-09-01 08:00:01 blood 2361 #> 4722 34.9 9 1945 1945-09-01 08:00:01 bone 2361 #> 4723 68.8 10 1945 1945-10-01 18:00:00 blood 2362 #> 4724 68.8 10 1945 1945-10-01 18:00:00 bone 2362 #> 4725 46.0 11 1945 1945-11-01 04:00:01 blood 2363 #> 4726 46.0 11 1945 1945-11-01 04:00:01 bone 2363 #> 4727 27.4 12 1945 1945-12-01 14:00:01 blood 2364 #> 4728 27.4 12 1945 1945-12-01 14:00:01 bone 2364 #> 4729 47.6 1 1946 1946-01-01 00:00:00 blood 2365 #> 4730 47.6 1 1946 1946-01-01 00:00:00 bone 2365 #> 4731 86.2 2 1946 1946-01-31 10:00:01 blood 2366 #> 4732 86.2 2 1946 1946-01-31 10:00:01 bone 2366 #> 4733 76.6 3 1946 1946-03-02 20:00:01 blood 2367 #> 4734 76.6 3 1946 1946-03-02 20:00:01 bone 2367 #> 4735 75.7 4 1946 1946-04-02 06:00:00 blood 2368 #> 4736 75.7 4 1946 1946-04-02 06:00:00 bone 2368 #> 4737 84.9 5 1946 1946-05-02 16:00:01 blood 2369 #> 4738 84.9 5 1946 1946-05-02 16:00:01 bone 2369 #> 4739 73.5 6 1946 1946-06-02 02:00:01 blood 2370 #> 4740 73.5 6 1946 1946-06-02 02:00:01 bone 2370 #> 4741 116.2 7 1946 1946-07-02 12:00:00 blood 2371 #> 4742 116.2 7 1946 1946-07-02 12:00:00 bone 2371 #> 4743 107.2 8 1946 1946-08-01 22:00:01 blood 2372 #> 4744 107.2 8 1946 1946-08-01 22:00:01 bone 2372 #> 4745 94.4 9 1946 1946-09-01 08:00:01 blood 2373 #> 4746 94.4 9 1946 1946-09-01 08:00:01 bone 2373 #> 4747 102.3 10 1946 1946-10-01 18:00:00 blood 2374 #> 4748 102.3 10 1946 1946-10-01 18:00:00 bone 2374 #> 4749 123.8 11 1946 1946-11-01 04:00:01 blood 2375 #> 4750 123.8 11 1946 1946-11-01 04:00:01 bone 2375 #> 4751 121.7 12 1946 1946-12-01 14:00:01 blood 2376 #> 4752 121.7 12 1946 1946-12-01 14:00:01 bone 2376 #> 4753 115.7 1 1947 1947-01-01 00:00:00 blood 2377 #> 4754 115.7 1 1947 1947-01-01 00:00:00 bone 2377 #> 4755 113.4 2 1947 1947-01-31 10:00:01 blood 2378 #> 4756 113.4 2 1947 1947-01-31 10:00:01 bone 2378 #> 4757 129.8 3 1947 1947-03-02 20:00:01 blood 2379 #> 4758 129.8 3 1947 1947-03-02 20:00:01 bone 2379 #> 4759 149.8 4 1947 1947-04-02 06:00:00 blood 2380 #> 4760 149.8 4 1947 1947-04-02 06:00:00 bone 2380 #> 4761 201.3 5 1947 1947-05-02 16:00:01 blood 2381 #> 4762 201.3 5 1947 1947-05-02 16:00:01 bone 2381 #> 4763 163.9 6 1947 1947-06-02 02:00:01 blood 2382 #> 4764 163.9 6 1947 1947-06-02 02:00:01 bone 2382 #> 4765 157.9 7 1947 1947-07-02 12:00:00 blood 2383 #> 4766 157.9 7 1947 1947-07-02 12:00:00 bone 2383 #> 4767 188.8 8 1947 1947-08-01 22:00:01 blood 2384 #> 4768 188.8 8 1947 1947-08-01 22:00:01 bone 2384 #> 4769 169.4 9 1947 1947-09-01 08:00:01 blood 2385 #> 4770 169.4 9 1947 1947-09-01 08:00:01 bone 2385 #> 4771 163.6 10 1947 1947-10-01 18:00:00 blood 2386 #> 4772 163.6 10 1947 1947-10-01 18:00:00 bone 2386 #> 4773 128.0 11 1947 1947-11-01 04:00:01 blood 2387 #> 4774 128.0 11 1947 1947-11-01 04:00:01 bone 2387 #> 4775 116.5 12 1947 1947-12-01 14:00:01 blood 2388 #> 4776 116.5 12 1947 1947-12-01 14:00:01 bone 2388 #> 4777 108.5 1 1948 1948-01-01 00:00:00 blood 2389 #> 4778 108.5 1 1948 1948-01-01 00:00:00 bone 2389 #> 4779 86.1 2 1948 1948-01-31 12:00:01 blood 2390 #> 4780 86.1 2 1948 1948-01-31 12:00:01 bone 2390 #> 4781 94.8 3 1948 1948-03-02 00:00:01 blood 2391 #> 4782 94.8 3 1948 1948-03-02 00:00:01 bone 2391 #> 4783 189.7 4 1948 1948-04-01 12:00:00 blood 2392 #> 4784 189.7 4 1948 1948-04-01 12:00:00 bone 2392 #> 4785 174.0 5 1948 1948-05-02 00:00:01 blood 2393 #> 4786 174.0 5 1948 1948-05-02 00:00:01 bone 2393 #> 4787 167.8 6 1948 1948-06-01 12:00:01 blood 2394 #> 4788 167.8 6 1948 1948-06-01 12:00:01 bone 2394 #> 4789 142.2 7 1948 1948-07-02 00:00:00 blood 2395 #> 4790 142.2 7 1948 1948-07-02 00:00:00 bone 2395 #> 4791 157.9 8 1948 1948-08-01 12:00:01 blood 2396 #> 4792 157.9 8 1948 1948-08-01 12:00:01 bone 2396 #> 4793 143.3 9 1948 1948-09-01 00:00:01 blood 2397 #> 4794 143.3 9 1948 1948-09-01 00:00:01 bone 2397 #> #> $data_test #> y season year date series time #> 1 136.3 10 1948 1948-10-01 12:00:00 blood 2398 #> 2 136.3 10 1948 1948-10-01 12:00:00 bone 2398 #> 3 95.8 11 1948 1948-11-01 00:00:01 blood 2399 #> 4 95.8 11 1948 1948-11-01 00:00:01 bone 2399 #> 5 138.0 12 1948 1948-12-01 12:00:01 blood 2400 #> 6 138.0 12 1948 1948-12-01 12:00:01 bone 2400 #> 7 119.1 1 1949 1949-01-01 00:00:00 blood 2401 #> 8 119.1 1 1949 1949-01-01 00:00:00 bone 2401 #> 9 182.3 2 1949 1949-01-31 10:00:01 blood 2402 #> 10 182.3 2 1949 1949-01-31 10:00:01 bone 2402 #> 11 157.5 3 1949 1949-03-02 20:00:01 blood 2403 #> 12 157.5 3 1949 1949-03-02 20:00:01 bone 2403 #> 13 147.0 4 1949 1949-04-02 06:00:00 blood 2404 #> 14 147.0 4 1949 1949-04-02 06:00:00 bone 2404 #> 15 106.2 5 1949 1949-05-02 16:00:01 blood 2405 #> 16 106.2 5 1949 1949-05-02 16:00:01 bone 2405 #> 17 121.7 6 1949 1949-06-02 02:00:01 blood 2406 #> 18 121.7 6 1949 1949-06-02 02:00:01 bone 2406 #> 19 125.8 7 1949 1949-07-02 12:00:00 blood 2407 #> 20 125.8 7 1949 1949-07-02 12:00:00 bone 2407 #> 21 123.8 8 1949 1949-08-01 22:00:01 blood 2408 #> 22 123.8 8 1949 1949-08-01 22:00:01 bone 2408 #> 23 145.3 9 1949 1949-09-01 08:00:01 blood 2409 #> 24 145.3 9 1949 1949-09-01 08:00:01 bone 2409 #> 25 131.6 10 1949 1949-10-01 18:00:00 blood 2410 #> 26 131.6 10 1949 1949-10-01 18:00:00 bone 2410 #> 27 143.5 11 1949 1949-11-01 04:00:01 blood 2411 #> 28 143.5 11 1949 1949-11-01 04:00:01 bone 2411 #> 29 117.6 12 1949 1949-12-01 14:00:01 blood 2412 #> 30 117.6 12 1949 1949-12-01 14:00:01 bone 2412 #> 31 101.6 1 1950 1950-01-01 00:00:00 blood 2413 #> 32 101.6 1 1950 1950-01-01 00:00:00 bone 2413 #> 33 94.8 2 1950 1950-01-31 10:00:01 blood 2414 #> 34 94.8 2 1950 1950-01-31 10:00:01 bone 2414 #> 35 109.7 3 1950 1950-03-02 20:00:01 blood 2415 #> 36 109.7 3 1950 1950-03-02 20:00:01 bone 2415 #> 37 113.4 4 1950 1950-04-02 06:00:00 blood 2416 #> 38 113.4 4 1950 1950-04-02 06:00:00 bone 2416 #> 39 106.2 5 1950 1950-05-02 16:00:01 blood 2417 #> 40 106.2 5 1950 1950-05-02 16:00:01 bone 2417 #> 41 83.6 6 1950 1950-06-02 02:00:01 blood 2418 #> 42 83.6 6 1950 1950-06-02 02:00:01 bone 2418 #> 43 91.0 7 1950 1950-07-02 12:00:00 blood 2419 #> 44 91.0 7 1950 1950-07-02 12:00:00 bone 2419 #> 45 85.2 8 1950 1950-08-01 22:00:01 blood 2420 #> 46 85.2 8 1950 1950-08-01 22:00:01 bone 2420 #> 47 51.3 9 1950 1950-09-01 08:00:01 blood 2421 #> 48 51.3 9 1950 1950-09-01 08:00:01 bone 2421 #> 49 61.4 10 1950 1950-10-01 18:00:00 blood 2422 #> 50 61.4 10 1950 1950-10-01 18:00:00 bone 2422 #> 51 54.8 11 1950 1950-11-01 04:00:01 blood 2423 #> 52 54.8 11 1950 1950-11-01 04:00:01 bone 2423 #> 53 54.1 12 1950 1950-12-01 14:00:01 blood 2424 #> 54 54.1 12 1950 1950-12-01 14:00:01 bone 2424 #> 55 59.9 1 1951 1951-01-01 00:00:00 blood 2425 #> 56 59.9 1 1951 1951-01-01 00:00:00 bone 2425 #> 57 59.9 2 1951 1951-01-31 10:00:01 blood 2426 #> 58 59.9 2 1951 1951-01-31 10:00:01 bone 2426 #> 59 59.9 3 1951 1951-03-02 20:00:01 blood 2427 #> 60 59.9 3 1951 1951-03-02 20:00:01 bone 2427 #> 61 92.9 4 1951 1951-04-02 06:00:00 blood 2428 #> 62 92.9 4 1951 1951-04-02 06:00:00 bone 2428 #> 63 108.5 5 1951 1951-05-02 16:00:01 blood 2429 #> 64 108.5 5 1951 1951-05-02 16:00:01 bone 2429 #> 65 100.6 6 1951 1951-06-02 02:00:01 blood 2430 #> 66 100.6 6 1951 1951-06-02 02:00:01 bone 2430 #> 67 61.5 7 1951 1951-07-02 12:00:00 blood 2431 #> 68 61.5 7 1951 1951-07-02 12:00:00 bone 2431 #> 69 61.0 8 1951 1951-08-01 22:00:01 blood 2432 #> 70 61.0 8 1951 1951-08-01 22:00:01 bone 2432 #> 71 83.1 9 1951 1951-09-01 08:00:01 blood 2433 #> 72 83.1 9 1951 1951-09-01 08:00:01 bone 2433 #> 73 51.6 10 1951 1951-10-01 18:00:00 blood 2434 #> 74 51.6 10 1951 1951-10-01 18:00:00 bone 2434 #> 75 52.4 11 1951 1951-11-01 04:00:01 blood 2435 #> 76 52.4 11 1951 1951-11-01 04:00:01 bone 2435 #> 77 45.8 12 1951 1951-12-01 14:00:01 blood 2436 #> 78 45.8 12 1951 1951-12-01 14:00:01 bone 2436 #> 79 40.7 1 1952 1952-01-01 00:00:00 blood 2437 #> 80 40.7 1 1952 1952-01-01 00:00:00 bone 2437 #> 81 22.7 2 1952 1952-01-31 12:00:01 blood 2438 #> 82 22.7 2 1952 1952-01-31 12:00:01 bone 2438 #> 83 22.0 3 1952 1952-03-02 00:00:01 blood 2439 #> 84 22.0 3 1952 1952-03-02 00:00:01 bone 2439 #> 85 29.1 4 1952 1952-04-01 12:00:00 blood 2440 #> 86 29.1 4 1952 1952-04-01 12:00:00 bone 2440 #> 87 23.4 5 1952 1952-05-02 00:00:01 blood 2441 #> 88 23.4 5 1952 1952-05-02 00:00:01 bone 2441 #> 89 36.4 6 1952 1952-06-01 12:00:01 blood 2442 #> 90 36.4 6 1952 1952-06-01 12:00:01 bone 2442 #> 91 39.3 7 1952 1952-07-02 00:00:00 blood 2443 #> 92 39.3 7 1952 1952-07-02 00:00:00 bone 2443 #> 93 54.9 8 1952 1952-08-01 12:00:01 blood 2444 #> 94 54.9 8 1952 1952-08-01 12:00:01 bone 2444 #> 95 28.2 9 1952 1952-09-01 00:00:01 blood 2445 #> 96 28.2 9 1952 1952-09-01 00:00:01 bone 2445 #> 97 23.8 10 1952 1952-10-01 12:00:00 blood 2446 #> 98 23.8 10 1952 1952-10-01 12:00:00 bone 2446 #> 99 22.1 11 1952 1952-11-01 00:00:01 blood 2447 #> 100 22.1 11 1952 1952-11-01 00:00:01 bone 2447 #> 101 34.3 12 1952 1952-12-01 12:00:01 blood 2448 #> 102 34.3 12 1952 1952-12-01 12:00:01 bone 2448 #> 103 26.5 1 1953 1953-01-01 00:00:00 blood 2449 #> 104 26.5 1 1953 1953-01-01 00:00:00 bone 2449 #> 105 3.9 2 1953 1953-01-31 10:00:01 blood 2450 #> 106 3.9 2 1953 1953-01-31 10:00:01 bone 2450 #> 107 10.0 3 1953 1953-03-02 20:00:01 blood 2451 #> 108 10.0 3 1953 1953-03-02 20:00:01 bone 2451 #> 109 27.8 4 1953 1953-04-02 06:00:00 blood 2452 #> 110 27.8 4 1953 1953-04-02 06:00:00 bone 2452 #> 111 12.5 5 1953 1953-05-02 16:00:01 blood 2453 #> 112 12.5 5 1953 1953-05-02 16:00:01 bone 2453 #> 113 21.8 6 1953 1953-06-02 02:00:01 blood 2454 #> 114 21.8 6 1953 1953-06-02 02:00:01 bone 2454 #> 115 8.6 7 1953 1953-07-02 12:00:00 blood 2455 #> 116 8.6 7 1953 1953-07-02 12:00:00 bone 2455 #> 117 23.5 8 1953 1953-08-01 22:00:01 blood 2456 #> 118 23.5 8 1953 1953-08-01 22:00:01 bone 2456 #> 119 19.3 9 1953 1953-09-01 08:00:01 blood 2457 #> 120 19.3 9 1953 1953-09-01 08:00:01 bone 2457 #> 121 8.2 10 1953 1953-10-01 18:00:00 blood 2458 #> 122 8.2 10 1953 1953-10-01 18:00:00 bone 2458 #> 123 1.6 11 1953 1953-11-01 04:00:01 blood 2459 #> 124 1.6 11 1953 1953-11-01 04:00:01 bone 2459 #> 125 2.5 12 1953 1953-12-01 14:00:01 blood 2460 #> 126 2.5 12 1953 1953-12-01 14:00:01 bone 2460 #> 127 0.2 1 1954 1954-01-01 00:00:00 blood 2461 #> 128 0.2 1 1954 1954-01-01 00:00:00 bone 2461 #> 129 0.5 2 1954 1954-01-31 10:00:01 blood 2462 #> 130 0.5 2 1954 1954-01-31 10:00:01 bone 2462 #> 131 10.9 3 1954 1954-03-02 20:00:01 blood 2463 #> 132 10.9 3 1954 1954-03-02 20:00:01 bone 2463 #> 133 1.8 4 1954 1954-04-02 06:00:00 blood 2464 #> 134 1.8 4 1954 1954-04-02 06:00:00 bone 2464 #> 135 0.8 5 1954 1954-05-02 16:00:01 blood 2465 #> 136 0.8 5 1954 1954-05-02 16:00:01 bone 2465 #> 137 0.2 6 1954 1954-06-02 02:00:01 blood 2466 #> 138 0.2 6 1954 1954-06-02 02:00:01 bone 2466 #> 139 4.8 7 1954 1954-07-02 12:00:00 blood 2467 #> 140 4.8 7 1954 1954-07-02 12:00:00 bone 2467 #> 141 8.4 8 1954 1954-08-01 22:00:01 blood 2468 #> 142 8.4 8 1954 1954-08-01 22:00:01 bone 2468 #> 143 1.5 9 1954 1954-09-01 08:00:01 blood 2469 #> 144 1.5 9 1954 1954-09-01 08:00:01 bone 2469 #> 145 7.0 10 1954 1954-10-01 18:00:00 blood 2470 #> 146 7.0 10 1954 1954-10-01 18:00:00 bone 2470 #> 147 9.2 11 1954 1954-11-01 04:00:01 blood 2471 #> 148 9.2 11 1954 1954-11-01 04:00:01 bone 2471 #> 149 7.6 12 1954 1954-12-01 14:00:01 blood 2472 #> 150 7.6 12 1954 1954-12-01 14:00:01 bone 2472 #> 151 23.1 1 1955 1955-01-01 00:00:00 blood 2473 #> 152 23.1 1 1955 1955-01-01 00:00:00 bone 2473 #> 153 20.8 2 1955 1955-01-31 10:00:01 blood 2474 #> 154 20.8 2 1955 1955-01-31 10:00:01 bone 2474 #> 155 4.9 3 1955 1955-03-02 20:00:01 blood 2475 #> 156 4.9 3 1955 1955-03-02 20:00:01 bone 2475 #> 157 11.3 4 1955 1955-04-02 06:00:00 blood 2476 #> 158 11.3 4 1955 1955-04-02 06:00:00 bone 2476 #> 159 28.9 5 1955 1955-05-02 16:00:01 blood 2477 #> 160 28.9 5 1955 1955-05-02 16:00:01 bone 2477 #> 161 31.7 6 1955 1955-06-02 02:00:01 blood 2478 #> 162 31.7 6 1955 1955-06-02 02:00:01 bone 2478 #> 163 26.7 7 1955 1955-07-02 12:00:00 blood 2479 #> 164 26.7 7 1955 1955-07-02 12:00:00 bone 2479 #> 165 40.7 8 1955 1955-08-01 22:00:01 blood 2480 #> 166 40.7 8 1955 1955-08-01 22:00:01 bone 2480 #> 167 42.7 9 1955 1955-09-01 08:00:01 blood 2481 #> 168 42.7 9 1955 1955-09-01 08:00:01 bone 2481 #> 169 58.5 10 1955 1955-10-01 18:00:00 blood 2482 #> 170 58.5 10 1955 1955-10-01 18:00:00 bone 2482 #> 171 89.2 11 1955 1955-11-01 04:00:01 blood 2483 #> 172 89.2 11 1955 1955-11-01 04:00:01 bone 2483 #> 173 76.9 12 1955 1955-12-01 14:00:01 blood 2484 #> 174 76.9 12 1955 1955-12-01 14:00:01 bone 2484 #> 175 73.6 1 1956 1956-01-01 00:00:00 blood 2485 #> 176 73.6 1 1956 1956-01-01 00:00:00 bone 2485 #> 177 124.0 2 1956 1956-01-31 12:00:01 blood 2486 #> 178 124.0 2 1956 1956-01-31 12:00:01 bone 2486 #> 179 118.4 3 1956 1956-03-02 00:00:01 blood 2487 #> 180 118.4 3 1956 1956-03-02 00:00:01 bone 2487 #> 181 110.7 4 1956 1956-04-01 12:00:00 blood 2488 #> 182 110.7 4 1956 1956-04-01 12:00:00 bone 2488 #> 183 136.6 5 1956 1956-05-02 00:00:01 blood 2489 #> 184 136.6 5 1956 1956-05-02 00:00:01 bone 2489 #> 185 116.6 6 1956 1956-06-01 12:00:01 blood 2490 #> 186 116.6 6 1956 1956-06-01 12:00:01 bone 2490 #> 187 129.1 7 1956 1956-07-02 00:00:00 blood 2491 #> 188 129.1 7 1956 1956-07-02 00:00:00 bone 2491 #> 189 169.6 8 1956 1956-08-01 12:00:01 blood 2492 #> 190 169.6 8 1956 1956-08-01 12:00:01 bone 2492 #> 191 173.2 9 1956 1956-09-01 00:00:01 blood 2493 #> 192 173.2 9 1956 1956-09-01 00:00:01 bone 2493 #> 193 155.3 10 1956 1956-10-01 12:00:00 blood 2494 #> 194 155.3 10 1956 1956-10-01 12:00:00 bone 2494 #> 195 201.3 11 1956 1956-11-01 00:00:01 blood 2495 #> 196 201.3 11 1956 1956-11-01 00:00:01 bone 2495 #> 197 192.1 12 1956 1956-12-01 12:00:01 blood 2496 #> 198 192.1 12 1956 1956-12-01 12:00:01 bone 2496 #> 199 165.0 1 1957 1957-01-01 00:00:00 blood 2497 #> 200 165.0 1 1957 1957-01-01 00:00:00 bone 2497 #> 201 130.2 2 1957 1957-01-31 10:00:01 blood 2498 #> 202 130.2 2 1957 1957-01-31 10:00:01 bone 2498 #> 203 157.4 3 1957 1957-03-02 20:00:01 blood 2499 #> 204 157.4 3 1957 1957-03-02 20:00:01 bone 2499 #> 205 175.2 4 1957 1957-04-02 06:00:00 blood 2500 #> 206 175.2 4 1957 1957-04-02 06:00:00 bone 2500 #> 207 164.6 5 1957 1957-05-02 16:00:01 blood 2501 #> 208 164.6 5 1957 1957-05-02 16:00:01 bone 2501 #> 209 200.7 6 1957 1957-06-02 02:00:01 blood 2502 #> 210 200.7 6 1957 1957-06-02 02:00:01 bone 2502 #> 211 187.2 7 1957 1957-07-02 12:00:00 blood 2503 #> 212 187.2 7 1957 1957-07-02 12:00:00 bone 2503 #> 213 158.0 8 1957 1957-08-01 22:00:01 blood 2504 #> 214 158.0 8 1957 1957-08-01 22:00:01 bone 2504 #> 215 235.8 9 1957 1957-09-01 08:00:01 blood 2505 #> 216 235.8 9 1957 1957-09-01 08:00:01 bone 2505 #> 217 253.8 10 1957 1957-10-01 18:00:00 blood 2506 #> 218 253.8 10 1957 1957-10-01 18:00:00 bone 2506 #> 219 210.9 11 1957 1957-11-01 04:00:01 blood 2507 #> 220 210.9 11 1957 1957-11-01 04:00:01 bone 2507 #> 221 239.4 12 1957 1957-12-01 14:00:01 blood 2508 #> 222 239.4 12 1957 1957-12-01 14:00:01 bone 2508 #> 223 202.5 1 1958 1958-01-01 00:00:00 blood 2509 #> 224 202.5 1 1958 1958-01-01 00:00:00 bone 2509 #> 225 164.9 2 1958 1958-01-31 10:00:01 blood 2510 #> 226 164.9 2 1958 1958-01-31 10:00:01 bone 2510 #> 227 190.7 3 1958 1958-03-02 20:00:01 blood 2511 #> 228 190.7 3 1958 1958-03-02 20:00:01 bone 2511 #> 229 196.0 4 1958 1958-04-02 06:00:00 blood 2512 #> 230 196.0 4 1958 1958-04-02 06:00:00 bone 2512 #> 231 175.3 5 1958 1958-05-02 16:00:01 blood 2513 #> 232 175.3 5 1958 1958-05-02 16:00:01 bone 2513 #> 233 171.5 6 1958 1958-06-02 02:00:01 blood 2514 #> 234 171.5 6 1958 1958-06-02 02:00:01 bone 2514 #> 235 191.4 7 1958 1958-07-02 12:00:00 blood 2515 #> 236 191.4 7 1958 1958-07-02 12:00:00 bone 2515 #> 237 200.2 8 1958 1958-08-01 22:00:01 blood 2516 #> 238 200.2 8 1958 1958-08-01 22:00:01 bone 2516 #> 239 201.2 9 1958 1958-09-01 08:00:01 blood 2517 #> 240 201.2 9 1958 1958-09-01 08:00:01 bone 2517 #> 241 181.5 10 1958 1958-10-01 18:00:00 blood 2518 #> 242 181.5 10 1958 1958-10-01 18:00:00 bone 2518 #> 243 152.3 11 1958 1958-11-01 04:00:01 blood 2519 #> 244 152.3 11 1958 1958-11-01 04:00:01 bone 2519 #> 245 187.6 12 1958 1958-12-01 14:00:01 blood 2520 #> 246 187.6 12 1958 1958-12-01 14:00:01 bone 2520 #> 247 217.4 1 1959 1959-01-01 00:00:00 blood 2521 #> 248 217.4 1 1959 1959-01-01 00:00:00 bone 2521 #> 249 143.1 2 1959 1959-01-31 10:00:01 blood 2522 #> 250 143.1 2 1959 1959-01-31 10:00:01 bone 2522 #> 251 185.7 3 1959 1959-03-02 20:00:01 blood 2523 #> 252 185.7 3 1959 1959-03-02 20:00:01 bone 2523 #> 253 163.3 4 1959 1959-04-02 06:00:00 blood 2524 #> 254 163.3 4 1959 1959-04-02 06:00:00 bone 2524 #> 255 172.0 5 1959 1959-05-02 16:00:01 blood 2525 #> 256 172.0 5 1959 1959-05-02 16:00:01 bone 2525 #> 257 168.7 6 1959 1959-06-02 02:00:01 blood 2526 #> 258 168.7 6 1959 1959-06-02 02:00:01 bone 2526 #> 259 149.6 7 1959 1959-07-02 12:00:00 blood 2527 #> 260 149.6 7 1959 1959-07-02 12:00:00 bone 2527 #> 261 199.6 8 1959 1959-08-01 22:00:01 blood 2528 #> 262 199.6 8 1959 1959-08-01 22:00:01 bone 2528 #> 263 145.2 9 1959 1959-09-01 08:00:01 blood 2529 #> 264 145.2 9 1959 1959-09-01 08:00:01 bone 2529 #> 265 111.4 10 1959 1959-10-01 18:00:00 blood 2530 #> 266 111.4 10 1959 1959-10-01 18:00:00 bone 2530 #> 267 124.0 11 1959 1959-11-01 04:00:01 blood 2531 #> 268 124.0 11 1959 1959-11-01 04:00:01 bone 2531 #> 269 125.0 12 1959 1959-12-01 14:00:01 blood 2532 #> 270 125.0 12 1959 1959-12-01 14:00:01 bone 2532 #> 271 146.3 1 1960 1960-01-01 00:00:00 blood 2533 #> 272 146.3 1 1960 1960-01-01 00:00:00 bone 2533 #> 273 106.0 2 1960 1960-01-31 12:00:01 blood 2534 #> 274 106.0 2 1960 1960-01-31 12:00:01 bone 2534 #> 275 102.2 3 1960 1960-03-02 00:00:01 blood 2535 #> 276 102.2 3 1960 1960-03-02 00:00:01 bone 2535 #> 277 122.0 4 1960 1960-04-01 12:00:00 blood 2536 #> 278 122.0 4 1960 1960-04-01 12:00:00 bone 2536 #> 279 119.6 5 1960 1960-05-02 00:00:01 blood 2537 #> 280 119.6 5 1960 1960-05-02 00:00:01 bone 2537 #> 281 110.2 6 1960 1960-06-01 12:00:01 blood 2538 #> 282 110.2 6 1960 1960-06-01 12:00:01 bone 2538 #> 283 121.7 7 1960 1960-07-02 00:00:00 blood 2539 #> 284 121.7 7 1960 1960-07-02 00:00:00 bone 2539 #> 285 134.1 8 1960 1960-08-01 12:00:01 blood 2540 #> 286 134.1 8 1960 1960-08-01 12:00:01 bone 2540 #> 287 127.2 9 1960 1960-09-01 00:00:01 blood 2541 #> 288 127.2 9 1960 1960-09-01 00:00:01 bone 2541 #> 289 82.8 10 1960 1960-10-01 12:00:00 blood 2542 #> 290 82.8 10 1960 1960-10-01 12:00:00 bone 2542 #> 291 89.6 11 1960 1960-11-01 00:00:01 blood 2543 #> 292 89.6 11 1960 1960-11-01 00:00:01 bone 2543 #> 293 85.6 12 1960 1960-12-01 12:00:01 blood 2544 #> 294 85.6 12 1960 1960-12-01 12:00:01 bone 2544 #> 295 57.9 1 1961 1961-01-01 00:00:00 blood 2545 #> 296 57.9 1 1961 1961-01-01 00:00:00 bone 2545 #> 297 46.1 2 1961 1961-01-31 10:00:01 blood 2546 #> 298 46.1 2 1961 1961-01-31 10:00:01 bone 2546 #> 299 53.0 3 1961 1961-03-02 20:00:01 blood 2547 #> 300 53.0 3 1961 1961-03-02 20:00:01 bone 2547 #> 301 61.4 4 1961 1961-04-02 06:00:00 blood 2548 #> 302 61.4 4 1961 1961-04-02 06:00:00 bone 2548 #> 303 51.0 5 1961 1961-05-02 16:00:01 blood 2549 #> 304 51.0 5 1961 1961-05-02 16:00:01 bone 2549 #> 305 77.4 6 1961 1961-06-02 02:00:01 blood 2550 #> 306 77.4 6 1961 1961-06-02 02:00:01 bone 2550 #> 307 70.2 7 1961 1961-07-02 12:00:00 blood 2551 #> 308 70.2 7 1961 1961-07-02 12:00:00 bone 2551 #> 309 55.9 8 1961 1961-08-01 22:00:01 blood 2552 #> 310 55.9 8 1961 1961-08-01 22:00:01 bone 2552 #> 311 63.6 9 1961 1961-09-01 08:00:01 blood 2553 #> 312 63.6 9 1961 1961-09-01 08:00:01 bone 2553 #> 313 37.7 10 1961 1961-10-01 18:00:00 blood 2554 #> 314 37.7 10 1961 1961-10-01 18:00:00 bone 2554 #> 315 32.6 11 1961 1961-11-01 04:00:01 blood 2555 #> 316 32.6 11 1961 1961-11-01 04:00:01 bone 2555 #> 317 40.0 12 1961 1961-12-01 14:00:01 blood 2556 #> 318 40.0 12 1961 1961-12-01 14:00:01 bone 2556 #> 319 38.7 1 1962 1962-01-01 00:00:00 blood 2557 #> 320 38.7 1 1962 1962-01-01 00:00:00 bone 2557 #> 321 50.3 2 1962 1962-01-31 10:00:01 blood 2558 #> 322 50.3 2 1962 1962-01-31 10:00:01 bone 2558 #> 323 45.6 3 1962 1962-03-02 20:00:01 blood 2559 #> 324 45.6 3 1962 1962-03-02 20:00:01 bone 2559 #> 325 46.4 4 1962 1962-04-02 06:00:00 blood 2560 #> 326 46.4 4 1962 1962-04-02 06:00:00 bone 2560 #> 327 43.7 5 1962 1962-05-02 16:00:01 blood 2561 #> 328 43.7 5 1962 1962-05-02 16:00:01 bone 2561 #> 329 42.0 6 1962 1962-06-02 02:00:01 blood 2562 #> 330 42.0 6 1962 1962-06-02 02:00:01 bone 2562 #> 331 21.8 7 1962 1962-07-02 12:00:00 blood 2563 #> 332 21.8 7 1962 1962-07-02 12:00:00 bone 2563 #> 333 21.8 8 1962 1962-08-01 22:00:01 blood 2564 #> 334 21.8 8 1962 1962-08-01 22:00:01 bone 2564 #> 335 51.3 9 1962 1962-09-01 08:00:01 blood 2565 #> 336 51.3 9 1962 1962-09-01 08:00:01 bone 2565 #> 337 39.5 10 1962 1962-10-01 18:00:00 blood 2566 #> 338 39.5 10 1962 1962-10-01 18:00:00 bone 2566 #> 339 26.9 11 1962 1962-11-01 04:00:01 blood 2567 #> 340 26.9 11 1962 1962-11-01 04:00:01 bone 2567 #> 341 23.2 12 1962 1962-12-01 14:00:01 blood 2568 #> 342 23.2 12 1962 1962-12-01 14:00:01 bone 2568 #> 343 19.8 1 1963 1963-01-01 00:00:00 blood 2569 #> 344 19.8 1 1963 1963-01-01 00:00:00 bone 2569 #> 345 24.4 2 1963 1963-01-31 10:00:01 blood 2570 #> 346 24.4 2 1963 1963-01-31 10:00:01 bone 2570 #> 347 17.1 3 1963 1963-03-02 20:00:01 blood 2571 #> 348 17.1 3 1963 1963-03-02 20:00:01 bone 2571 #> 349 29.3 4 1963 1963-04-02 06:00:00 blood 2572 #> 350 29.3 4 1963 1963-04-02 06:00:00 bone 2572 #> 351 43.0 5 1963 1963-05-02 16:00:01 blood 2573 #> 352 43.0 5 1963 1963-05-02 16:00:01 bone 2573 #> 353 35.9 6 1963 1963-06-02 02:00:01 blood 2574 #> 354 35.9 6 1963 1963-06-02 02:00:01 bone 2574 #> 355 19.6 7 1963 1963-07-02 12:00:00 blood 2575 #> 356 19.6 7 1963 1963-07-02 12:00:00 bone 2575 #> 357 33.2 8 1963 1963-08-01 22:00:01 blood 2576 #> 358 33.2 8 1963 1963-08-01 22:00:01 bone 2576 #> 359 38.8 9 1963 1963-09-01 08:00:01 blood 2577 #> 360 38.8 9 1963 1963-09-01 08:00:01 bone 2577 #> 361 35.3 10 1963 1963-10-01 18:00:00 blood 2578 #> 362 35.3 10 1963 1963-10-01 18:00:00 bone 2578 #> 363 23.4 11 1963 1963-11-01 04:00:01 blood 2579 #> 364 23.4 11 1963 1963-11-01 04:00:01 bone 2579 #> 365 14.9 12 1963 1963-12-01 14:00:01 blood 2580 #> 366 14.9 12 1963 1963-12-01 14:00:01 bone 2580 #> 367 15.3 1 1964 1964-01-01 00:00:00 blood 2581 #> 368 15.3 1 1964 1964-01-01 00:00:00 bone 2581 #> 369 17.7 2 1964 1964-01-31 12:00:01 blood 2582 #> 370 17.7 2 1964 1964-01-31 12:00:01 bone 2582 #> 371 16.5 3 1964 1964-03-02 00:00:01 blood 2583 #> 372 16.5 3 1964 1964-03-02 00:00:01 bone 2583 #> 373 8.6 4 1964 1964-04-01 12:00:00 blood 2584 #> 374 8.6 4 1964 1964-04-01 12:00:00 bone 2584 #> 375 9.5 5 1964 1964-05-02 00:00:01 blood 2585 #> 376 9.5 5 1964 1964-05-02 00:00:01 bone 2585 #> 377 9.1 6 1964 1964-06-01 12:00:01 blood 2586 #> 378 9.1 6 1964 1964-06-01 12:00:01 bone 2586 #> 379 3.1 7 1964 1964-07-02 00:00:00 blood 2587 #> 380 3.1 7 1964 1964-07-02 00:00:00 bone 2587 #> 381 9.3 8 1964 1964-08-01 12:00:01 blood 2588 #> 382 9.3 8 1964 1964-08-01 12:00:01 bone 2588 #> 383 4.7 9 1964 1964-09-01 00:00:01 blood 2589 #> 384 4.7 9 1964 1964-09-01 00:00:01 bone 2589 #> 385 6.1 10 1964 1964-10-01 12:00:00 blood 2590 #> 386 6.1 10 1964 1964-10-01 12:00:00 bone 2590 #> 387 7.4 11 1964 1964-11-01 00:00:01 blood 2591 #> 388 7.4 11 1964 1964-11-01 00:00:01 bone 2591 #> 389 15.1 12 1964 1964-12-01 12:00:01 blood 2592 #> 390 15.1 12 1964 1964-12-01 12:00:01 bone 2592 #> 391 17.5 1 1965 1965-01-01 00:00:00 blood 2593 #> 392 17.5 1 1965 1965-01-01 00:00:00 bone 2593 #> 393 14.2 2 1965 1965-01-31 10:00:01 blood 2594 #> 394 14.2 2 1965 1965-01-31 10:00:01 bone 2594 #> 395 11.7 3 1965 1965-03-02 20:00:01 blood 2595 #> 396 11.7 3 1965 1965-03-02 20:00:01 bone 2595 #> 397 6.8 4 1965 1965-04-02 06:00:00 blood 2596 #> 398 6.8 4 1965 1965-04-02 06:00:00 bone 2596 #> 399 24.1 5 1965 1965-05-02 16:00:01 blood 2597 #> 400 24.1 5 1965 1965-05-02 16:00:01 bone 2597 #> 401 15.9 6 1965 1965-06-02 02:00:01 blood 2598 #> 402 15.9 6 1965 1965-06-02 02:00:01 bone 2598 #> 403 11.9 7 1965 1965-07-02 12:00:00 blood 2599 #> 404 11.9 7 1965 1965-07-02 12:00:00 bone 2599 #> 405 8.9 8 1965 1965-08-01 22:00:01 blood 2600 #> 406 8.9 8 1965 1965-08-01 22:00:01 bone 2600 #> 407 16.8 9 1965 1965-09-01 08:00:01 blood 2601 #> 408 16.8 9 1965 1965-09-01 08:00:01 bone 2601 #> 409 20.1 10 1965 1965-10-01 18:00:00 blood 2602 #> 410 20.1 10 1965 1965-10-01 18:00:00 bone 2602 #> 411 15.8 11 1965 1965-11-01 04:00:01 blood 2603 #> 412 15.8 11 1965 1965-11-01 04:00:01 bone 2603 #> 413 17.0 12 1965 1965-12-01 14:00:01 blood 2604 #> 414 17.0 12 1965 1965-12-01 14:00:01 bone 2604 #> 415 28.2 1 1966 1966-01-01 00:00:00 blood 2605 #> 416 28.2 1 1966 1966-01-01 00:00:00 bone 2605 #> 417 24.4 2 1966 1966-01-31 10:00:01 blood 2606 #> 418 24.4 2 1966 1966-01-31 10:00:01 bone 2606 #> 419 25.3 3 1966 1966-03-02 20:00:01 blood 2607 #> 420 25.3 3 1966 1966-03-02 20:00:01 bone 2607 #> 421 48.7 4 1966 1966-04-02 06:00:00 blood 2608 #> 422 48.7 4 1966 1966-04-02 06:00:00 bone 2608 #> 423 45.3 5 1966 1966-05-02 16:00:01 blood 2609 #> 424 45.3 5 1966 1966-05-02 16:00:01 bone 2609 #> 425 47.7 6 1966 1966-06-02 02:00:01 blood 2610 #> 426 47.7 6 1966 1966-06-02 02:00:01 bone 2610 #> 427 56.7 7 1966 1966-07-02 12:00:00 blood 2611 #> 428 56.7 7 1966 1966-07-02 12:00:00 bone 2611 #> 429 51.2 8 1966 1966-08-01 22:00:01 blood 2612 #> 430 51.2 8 1966 1966-08-01 22:00:01 bone 2612 #> 431 50.2 9 1966 1966-09-01 08:00:01 blood 2613 #> 432 50.2 9 1966 1966-09-01 08:00:01 bone 2613 #> 433 57.2 10 1966 1966-10-01 18:00:00 blood 2614 #> 434 57.2 10 1966 1966-10-01 18:00:00 bone 2614 #> 435 57.2 11 1966 1966-11-01 04:00:01 blood 2615 #> 436 57.2 11 1966 1966-11-01 04:00:01 bone 2615 #> 437 70.4 12 1966 1966-12-01 14:00:01 blood 2616 #> 438 70.4 12 1966 1966-12-01 14:00:01 bone 2616 #> 439 110.9 1 1967 1967-01-01 00:00:00 blood 2617 #> 440 110.9 1 1967 1967-01-01 00:00:00 bone 2617 #> 441 93.6 2 1967 1967-01-31 10:00:01 blood 2618 #> 442 93.6 2 1967 1967-01-31 10:00:01 bone 2618 #> 443 111.8 3 1967 1967-03-02 20:00:01 blood 2619 #> 444 111.8 3 1967 1967-03-02 20:00:01 bone 2619 #> 445 69.5 4 1967 1967-04-02 06:00:00 blood 2620 #> 446 69.5 4 1967 1967-04-02 06:00:00 bone 2620 #> 447 86.5 5 1967 1967-05-02 16:00:01 blood 2621 #> 448 86.5 5 1967 1967-05-02 16:00:01 bone 2621 #> 449 67.3 6 1967 1967-06-02 02:00:01 blood 2622 #> 450 67.3 6 1967 1967-06-02 02:00:01 bone 2622 #> 451 91.5 7 1967 1967-07-02 12:00:00 blood 2623 #> 452 91.5 7 1967 1967-07-02 12:00:00 bone 2623 #> 453 107.2 8 1967 1967-08-01 22:00:01 blood 2624 #> 454 107.2 8 1967 1967-08-01 22:00:01 bone 2624 #> 455 76.8 9 1967 1967-09-01 08:00:01 blood 2625 #> 456 76.8 9 1967 1967-09-01 08:00:01 bone 2625 #> 457 88.2 10 1967 1967-10-01 18:00:00 blood 2626 #> 458 88.2 10 1967 1967-10-01 18:00:00 bone 2626 #> 459 94.3 11 1967 1967-11-01 04:00:01 blood 2627 #> 460 94.3 11 1967 1967-11-01 04:00:01 bone 2627 #> 461 126.4 12 1967 1967-12-01 14:00:01 blood 2628 #> 462 126.4 12 1967 1967-12-01 14:00:01 bone 2628 #> 463 121.8 1 1968 1968-01-01 00:00:00 blood 2629 #> 464 121.8 1 1968 1968-01-01 00:00:00 bone 2629 #> 465 111.9 2 1968 1968-01-31 12:00:01 blood 2630 #> 466 111.9 2 1968 1968-01-31 12:00:01 bone 2630 #> 467 92.2 3 1968 1968-03-02 00:00:01 blood 2631 #> 468 92.2 3 1968 1968-03-02 00:00:01 bone 2631 #> 469 81.2 4 1968 1968-04-01 12:00:00 blood 2632 #> 470 81.2 4 1968 1968-04-01 12:00:00 bone 2632 #> 471 127.2 5 1968 1968-05-02 00:00:01 blood 2633 #> 472 127.2 5 1968 1968-05-02 00:00:01 bone 2633 #> 473 110.3 6 1968 1968-06-01 12:00:01 blood 2634 #> 474 110.3 6 1968 1968-06-01 12:00:01 bone 2634 #> 475 96.1 7 1968 1968-07-02 00:00:00 blood 2635 #> 476 96.1 7 1968 1968-07-02 00:00:00 bone 2635 #> 477 109.3 8 1968 1968-08-01 12:00:01 blood 2636 #> 478 109.3 8 1968 1968-08-01 12:00:01 bone 2636 #> 479 117.2 9 1968 1968-09-01 00:00:01 blood 2637 #> 480 117.2 9 1968 1968-09-01 00:00:01 bone 2637 #> 481 107.7 10 1968 1968-10-01 12:00:00 blood 2638 #> 482 107.7 10 1968 1968-10-01 12:00:00 bone 2638 #> 483 86.0 11 1968 1968-11-01 00:00:01 blood 2639 #> 484 86.0 11 1968 1968-11-01 00:00:01 bone 2639 #> 485 109.8 12 1968 1968-12-01 12:00:01 blood 2640 #> 486 109.8 12 1968 1968-12-01 12:00:01 bone 2640 #> 487 104.4 1 1969 1969-01-01 00:00:00 blood 2641 #> 488 104.4 1 1969 1969-01-01 00:00:00 bone 2641 #> 489 120.5 2 1969 1969-01-31 10:00:01 blood 2642 #> 490 120.5 2 1969 1969-01-31 10:00:01 bone 2642 #> 491 135.8 3 1969 1969-03-02 20:00:01 blood 2643 #> 492 135.8 3 1969 1969-03-02 20:00:01 bone 2643 #> 493 106.8 4 1969 1969-04-02 06:00:00 blood 2644 #> 494 106.8 4 1969 1969-04-02 06:00:00 bone 2644 #> 495 120.0 5 1969 1969-05-02 16:00:01 blood 2645 #> 496 120.0 5 1969 1969-05-02 16:00:01 bone 2645 #> 497 106.0 6 1969 1969-06-02 02:00:01 blood 2646 #> 498 106.0 6 1969 1969-06-02 02:00:01 bone 2646 #> 499 96.8 7 1969 1969-07-02 12:00:00 blood 2647 #> 500 96.8 7 1969 1969-07-02 12:00:00 bone 2647 #> 501 98.0 8 1969 1969-08-01 22:00:01 blood 2648 #> 502 98.0 8 1969 1969-08-01 22:00:01 bone 2648 #> 503 91.3 9 1969 1969-09-01 08:00:01 blood 2649 #> 504 91.3 9 1969 1969-09-01 08:00:01 bone 2649 #> 505 95.7 10 1969 1969-10-01 18:00:00 blood 2650 #> 506 95.7 10 1969 1969-10-01 18:00:00 bone 2650 #> 507 93.5 11 1969 1969-11-01 04:00:01 blood 2651 #> 508 93.5 11 1969 1969-11-01 04:00:01 bone 2651 #> 509 97.9 12 1969 1969-12-01 14:00:01 blood 2652 #> 510 97.9 12 1969 1969-12-01 14:00:01 bone 2652 #> 511 111.5 1 1970 1970-01-01 00:00:00 blood 2653 #> 512 111.5 1 1970 1970-01-01 00:00:00 bone 2653 #> 513 127.8 2 1970 1970-01-31 10:00:00 blood 2654 #> 514 127.8 2 1970 1970-01-31 10:00:00 bone 2654 #> 515 102.9 3 1970 1970-03-02 20:00:00 blood 2655 #> 516 102.9 3 1970 1970-03-02 20:00:00 bone 2655 #> 517 109.5 4 1970 1970-04-02 06:00:00 blood 2656 #> 518 109.5 4 1970 1970-04-02 06:00:00 bone 2656 #> 519 127.5 5 1970 1970-05-02 16:00:00 blood 2657 #> 520 127.5 5 1970 1970-05-02 16:00:00 bone 2657 #> 521 106.8 6 1970 1970-06-02 02:00:00 blood 2658 #> 522 106.8 6 1970 1970-06-02 02:00:00 bone 2658 #> 523 112.5 7 1970 1970-07-02 12:00:00 blood 2659 #> 524 112.5 7 1970 1970-07-02 12:00:00 bone 2659 #> 525 93.0 8 1970 1970-08-01 22:00:00 blood 2660 #> 526 93.0 8 1970 1970-08-01 22:00:00 bone 2660 #> 527 99.5 9 1970 1970-09-01 08:00:00 blood 2661 #> 528 99.5 9 1970 1970-09-01 08:00:00 bone 2661 #> 529 86.6 10 1970 1970-10-01 18:00:00 blood 2662 #> 530 86.6 10 1970 1970-10-01 18:00:00 bone 2662 #> 531 95.2 11 1970 1970-11-01 04:00:00 blood 2663 #> 532 95.2 11 1970 1970-11-01 04:00:00 bone 2663 #> 533 83.5 12 1970 1970-12-01 14:00:00 blood 2664 #> 534 83.5 12 1970 1970-12-01 14:00:00 bone 2664 #> 535 91.3 1 1971 1971-01-01 00:00:00 blood 2665 #> 536 91.3 1 1971 1971-01-01 00:00:00 bone 2665 #> 537 79.0 2 1971 1971-01-31 10:00:00 blood 2666 #> 538 79.0 2 1971 1971-01-31 10:00:00 bone 2666 #> 539 60.7 3 1971 1971-03-02 20:00:00 blood 2667 #> 540 60.7 3 1971 1971-03-02 20:00:00 bone 2667 #> 541 71.8 4 1971 1971-04-02 06:00:00 blood 2668 #> 542 71.8 4 1971 1971-04-02 06:00:00 bone 2668 #> 543 57.5 5 1971 1971-05-02 16:00:00 blood 2669 #> 544 57.5 5 1971 1971-05-02 16:00:00 bone 2669 #> 545 49.8 6 1971 1971-06-02 02:00:00 blood 2670 #> 546 49.8 6 1971 1971-06-02 02:00:00 bone 2670 #> 547 81.0 7 1971 1971-07-02 12:00:00 blood 2671 #> 548 81.0 7 1971 1971-07-02 12:00:00 bone 2671 #> 549 61.4 8 1971 1971-08-01 22:00:00 blood 2672 #> 550 61.4 8 1971 1971-08-01 22:00:00 bone 2672 #> 551 50.2 9 1971 1971-09-01 08:00:00 blood 2673 #> 552 50.2 9 1971 1971-09-01 08:00:00 bone 2673 #> 553 51.7 10 1971 1971-10-01 18:00:00 blood 2674 #> 554 51.7 10 1971 1971-10-01 18:00:00 bone 2674 #> 555 63.2 11 1971 1971-11-01 04:00:00 blood 2675 #> 556 63.2 11 1971 1971-11-01 04:00:00 bone 2675 #> 557 82.2 12 1971 1971-12-01 14:00:00 blood 2676 #> 558 82.2 12 1971 1971-12-01 14:00:00 bone 2676 #> 559 61.5 1 1972 1972-01-01 00:00:00 blood 2677 #> 560 61.5 1 1972 1972-01-01 00:00:00 bone 2677 #> 561 88.4 2 1972 1972-01-31 12:00:00 blood 2678 #> 562 88.4 2 1972 1972-01-31 12:00:00 bone 2678 #> 563 80.1 3 1972 1972-03-02 00:00:00 blood 2679 #> 564 80.1 3 1972 1972-03-02 00:00:00 bone 2679 #> 565 63.2 4 1972 1972-04-01 12:00:00 blood 2680 #> 566 63.2 4 1972 1972-04-01 12:00:00 bone 2680 #> 567 80.5 5 1972 1972-05-02 00:00:00 blood 2681 #> 568 80.5 5 1972 1972-05-02 00:00:00 bone 2681 #> 569 88.0 6 1972 1972-06-01 12:00:00 blood 2682 #> 570 88.0 6 1972 1972-06-01 12:00:00 bone 2682 #> 571 76.5 7 1972 1972-07-02 00:00:00 blood 2683 #> 572 76.5 7 1972 1972-07-02 00:00:00 bone 2683 #> 573 76.8 8 1972 1972-08-01 12:00:00 blood 2684 #> 574 76.8 8 1972 1972-08-01 12:00:00 bone 2684 #> 575 64.0 9 1972 1972-09-01 00:00:00 blood 2685 #> 576 64.0 9 1972 1972-09-01 00:00:00 bone 2685 #> 577 61.3 10 1972 1972-10-01 12:00:00 blood 2686 #> 578 61.3 10 1972 1972-10-01 12:00:00 bone 2686 #> 579 41.6 11 1972 1972-11-01 00:00:00 blood 2687 #> 580 41.6 11 1972 1972-11-01 00:00:00 bone 2687 #> 581 45.3 12 1972 1972-12-01 12:00:00 blood 2688 #> 582 45.3 12 1972 1972-12-01 12:00:00 bone 2688 #> 583 43.4 1 1973 1973-01-01 00:00:00 blood 2689 #> 584 43.4 1 1973 1973-01-01 00:00:00 bone 2689 #> 585 42.9 2 1973 1973-01-31 10:00:00 blood 2690 #> 586 42.9 2 1973 1973-01-31 10:00:00 bone 2690 #> 587 46.0 3 1973 1973-03-02 20:00:00 blood 2691 #> 588 46.0 3 1973 1973-03-02 20:00:00 bone 2691 #> 589 57.7 4 1973 1973-04-02 06:00:00 blood 2692 #> 590 57.7 4 1973 1973-04-02 06:00:00 bone 2692 #> 591 42.4 5 1973 1973-05-02 16:00:00 blood 2693 #> 592 42.4 5 1973 1973-05-02 16:00:00 bone 2693 #> 593 39.5 6 1973 1973-06-02 02:00:00 blood 2694 #> 594 39.5 6 1973 1973-06-02 02:00:00 bone 2694 #> 595 23.1 7 1973 1973-07-02 12:00:00 blood 2695 #> 596 23.1 7 1973 1973-07-02 12:00:00 bone 2695 #> 597 25.6 8 1973 1973-08-01 22:00:00 blood 2696 #> 598 25.6 8 1973 1973-08-01 22:00:00 bone 2696 #> 599 59.3 9 1973 1973-09-01 08:00:00 blood 2697 #> 600 59.3 9 1973 1973-09-01 08:00:00 bone 2697 #> 601 30.7 10 1973 1973-10-01 18:00:00 blood 2698 #> 602 30.7 10 1973 1973-10-01 18:00:00 bone 2698 #> 603 23.9 11 1973 1973-11-01 04:00:00 blood 2699 #> 604 23.9 11 1973 1973-11-01 04:00:00 bone 2699 #> 605 23.3 12 1973 1973-12-01 14:00:00 blood 2700 #> 606 23.3 12 1973 1973-12-01 14:00:00 bone 2700 #> 607 27.6 1 1974 1974-01-01 00:00:00 blood 2701 #> 608 27.6 1 1974 1974-01-01 00:00:00 bone 2701 #> 609 26.0 2 1974 1974-01-31 10:00:00 blood 2702 #> 610 26.0 2 1974 1974-01-31 10:00:00 bone 2702 #> 611 21.3 3 1974 1974-03-02 20:00:00 blood 2703 #> 612 21.3 3 1974 1974-03-02 20:00:00 bone 2703 #> 613 40.3 4 1974 1974-04-02 06:00:00 blood 2704 #> 614 40.3 4 1974 1974-04-02 06:00:00 bone 2704 #> 615 39.5 5 1974 1974-05-02 16:00:00 blood 2705 #> 616 39.5 5 1974 1974-05-02 16:00:00 bone 2705 #> 617 36.0 6 1974 1974-06-02 02:00:00 blood 2706 #> 618 36.0 6 1974 1974-06-02 02:00:00 bone 2706 #> 619 55.8 7 1974 1974-07-02 12:00:00 blood 2707 #> 620 55.8 7 1974 1974-07-02 12:00:00 bone 2707 #> 621 33.6 8 1974 1974-08-01 22:00:00 blood 2708 #> 622 33.6 8 1974 1974-08-01 22:00:00 bone 2708 #> 623 40.2 9 1974 1974-09-01 08:00:00 blood 2709 #> 624 40.2 9 1974 1974-09-01 08:00:00 bone 2709 #> 625 47.1 10 1974 1974-10-01 18:00:00 blood 2710 #> 626 47.1 10 1974 1974-10-01 18:00:00 bone 2710 #> 627 25.0 11 1974 1974-11-01 04:00:00 blood 2711 #> 628 25.0 11 1974 1974-11-01 04:00:00 bone 2711 #> 629 20.5 12 1974 1974-12-01 14:00:00 blood 2712 #> 630 20.5 12 1974 1974-12-01 14:00:00 bone 2712 #> 631 18.9 1 1975 1975-01-01 00:00:00 blood 2713 #> 632 18.9 1 1975 1975-01-01 00:00:00 bone 2713 #> 633 11.5 2 1975 1975-01-31 10:00:00 blood 2714 #> 634 11.5 2 1975 1975-01-31 10:00:00 bone 2714 #> 635 11.5 3 1975 1975-03-02 20:00:00 blood 2715 #> 636 11.5 3 1975 1975-03-02 20:00:00 bone 2715 #> 637 5.1 4 1975 1975-04-02 06:00:00 blood 2716 #> 638 5.1 4 1975 1975-04-02 06:00:00 bone 2716 #> 639 9.0 5 1975 1975-05-02 16:00:00 blood 2717 #> 640 9.0 5 1975 1975-05-02 16:00:00 bone 2717 #> 641 11.4 6 1975 1975-06-02 02:00:00 blood 2718 #> 642 11.4 6 1975 1975-06-02 02:00:00 bone 2718 #> 643 28.2 7 1975 1975-07-02 12:00:00 blood 2719 #> 644 28.2 7 1975 1975-07-02 12:00:00 bone 2719 #> 645 39.7 8 1975 1975-08-01 22:00:00 blood 2720 #> 646 39.7 8 1975 1975-08-01 22:00:00 bone 2720 #> 647 13.9 9 1975 1975-09-01 08:00:00 blood 2721 #> 648 13.9 9 1975 1975-09-01 08:00:00 bone 2721 #> 649 9.1 10 1975 1975-10-01 18:00:00 blood 2722 #> 650 9.1 10 1975 1975-10-01 18:00:00 bone 2722 #> 651 19.4 11 1975 1975-11-01 04:00:00 blood 2723 #> 652 19.4 11 1975 1975-11-01 04:00:00 bone 2723 #> 653 7.8 12 1975 1975-12-01 14:00:00 blood 2724 #> 654 7.8 12 1975 1975-12-01 14:00:00 bone 2724 #> 655 8.1 1 1976 1976-01-01 00:00:00 blood 2725 #> 656 8.1 1 1976 1976-01-01 00:00:00 bone 2725 #> 657 4.3 2 1976 1976-01-31 12:00:00 blood 2726 #> 658 4.3 2 1976 1976-01-31 12:00:00 bone 2726 #> 659 21.9 3 1976 1976-03-02 00:00:00 blood 2727 #> 660 21.9 3 1976 1976-03-02 00:00:00 bone 2727 #> 661 18.8 4 1976 1976-04-01 12:00:00 blood 2728 #> 662 18.8 4 1976 1976-04-01 12:00:00 bone 2728 #> 663 12.4 5 1976 1976-05-02 00:00:00 blood 2729 #> 664 12.4 5 1976 1976-05-02 00:00:00 bone 2729 #> 665 12.2 6 1976 1976-06-01 12:00:00 blood 2730 #> 666 12.2 6 1976 1976-06-01 12:00:00 bone 2730 #> 667 1.9 7 1976 1976-07-02 00:00:00 blood 2731 #> 668 1.9 7 1976 1976-07-02 00:00:00 bone 2731 #> 669 16.4 8 1976 1976-08-01 12:00:00 blood 2732 #> 670 16.4 8 1976 1976-08-01 12:00:00 bone 2732 #> 671 13.5 9 1976 1976-09-01 00:00:00 blood 2733 #> 672 13.5 9 1976 1976-09-01 00:00:00 bone 2733 #> 673 20.6 10 1976 1976-10-01 12:00:00 blood 2734 #> 674 20.6 10 1976 1976-10-01 12:00:00 bone 2734 #> 675 5.2 11 1976 1976-11-01 00:00:00 blood 2735 #> 676 5.2 11 1976 1976-11-01 00:00:00 bone 2735 #> 677 15.3 12 1976 1976-12-01 12:00:00 blood 2736 #> 678 15.3 12 1976 1976-12-01 12:00:00 bone 2736 #> 679 16.4 1 1977 1977-01-01 00:00:00 blood 2737 #> 680 16.4 1 1977 1977-01-01 00:00:00 bone 2737 #> 681 23.1 2 1977 1977-01-31 10:00:00 blood 2738 #> 682 23.1 2 1977 1977-01-31 10:00:00 bone 2738 #> 683 8.7 3 1977 1977-03-02 20:00:00 blood 2739 #> 684 8.7 3 1977 1977-03-02 20:00:00 bone 2739 #> 685 12.9 4 1977 1977-04-02 06:00:00 blood 2740 #> 686 12.9 4 1977 1977-04-02 06:00:00 bone 2740 #> 687 18.6 5 1977 1977-05-02 16:00:00 blood 2741 #> 688 18.6 5 1977 1977-05-02 16:00:00 bone 2741 #> 689 38.5 6 1977 1977-06-02 02:00:00 blood 2742 #> 690 38.5 6 1977 1977-06-02 02:00:00 bone 2742 #> 691 21.4 7 1977 1977-07-02 12:00:00 blood 2743 #> 692 21.4 7 1977 1977-07-02 12:00:00 bone 2743 #> 693 30.1 8 1977 1977-08-01 22:00:00 blood 2744 #> 694 30.1 8 1977 1977-08-01 22:00:00 bone 2744 #> 695 44.0 9 1977 1977-09-01 08:00:00 blood 2745 #> 696 44.0 9 1977 1977-09-01 08:00:00 bone 2745 #> 697 43.8 10 1977 1977-10-01 18:00:00 blood 2746 #> 698 43.8 10 1977 1977-10-01 18:00:00 bone 2746 #> 699 29.1 11 1977 1977-11-01 04:00:00 blood 2747 #> 700 29.1 11 1977 1977-11-01 04:00:00 bone 2747 #> 701 43.2 12 1977 1977-12-01 14:00:00 blood 2748 #> 702 43.2 12 1977 1977-12-01 14:00:00 bone 2748 #> 703 51.9 1 1978 1978-01-01 00:00:00 blood 2749 #> 704 51.9 1 1978 1978-01-01 00:00:00 bone 2749 #> 705 93.6 2 1978 1978-01-31 10:00:00 blood 2750 #> 706 93.6 2 1978 1978-01-31 10:00:00 bone 2750 #> 707 76.5 3 1978 1978-03-02 20:00:00 blood 2751 #> 708 76.5 3 1978 1978-03-02 20:00:00 bone 2751 #> 709 99.7 4 1978 1978-04-02 06:00:00 blood 2752 #> 710 99.7 4 1978 1978-04-02 06:00:00 bone 2752 #> 711 82.7 5 1978 1978-05-02 16:00:00 blood 2753 #> 712 82.7 5 1978 1978-05-02 16:00:00 bone 2753 #> 713 95.1 6 1978 1978-06-02 02:00:00 blood 2754 #> 714 95.1 6 1978 1978-06-02 02:00:00 bone 2754 #> 715 70.4 7 1978 1978-07-02 12:00:00 blood 2755 #> 716 70.4 7 1978 1978-07-02 12:00:00 bone 2755 #> 717 58.1 8 1978 1978-08-01 22:00:00 blood 2756 #> 718 58.1 8 1978 1978-08-01 22:00:00 bone 2756 #> 719 138.2 9 1978 1978-09-01 08:00:00 blood 2757 #> 720 138.2 9 1978 1978-09-01 08:00:00 bone 2757 #> 721 125.1 10 1978 1978-10-01 18:00:00 blood 2758 #> 722 125.1 10 1978 1978-10-01 18:00:00 bone 2758 #> 723 97.9 11 1978 1978-11-01 04:00:00 blood 2759 #> 724 97.9 11 1978 1978-11-01 04:00:00 bone 2759 #> 725 122.7 12 1978 1978-12-01 14:00:00 blood 2760 #> 726 122.7 12 1978 1978-12-01 14:00:00 bone 2760 #> 727 166.6 1 1979 1979-01-01 00:00:00 blood 2761 #> 728 166.6 1 1979 1979-01-01 00:00:00 bone 2761 #> 729 137.5 2 1979 1979-01-31 10:00:00 blood 2762 #> 730 137.5 2 1979 1979-01-31 10:00:00 bone 2762 #> 731 138.0 3 1979 1979-03-02 20:00:00 blood 2763 #> 732 138.0 3 1979 1979-03-02 20:00:00 bone 2763 #> 733 101.5 4 1979 1979-04-02 06:00:00 blood 2764 #> 734 101.5 4 1979 1979-04-02 06:00:00 bone 2764 #> 735 134.4 5 1979 1979-05-02 16:00:00 blood 2765 #> 736 134.4 5 1979 1979-05-02 16:00:00 bone 2765 #> 737 149.5 6 1979 1979-06-02 02:00:00 blood 2766 #> 738 149.5 6 1979 1979-06-02 02:00:00 bone 2766 #> 739 159.4 7 1979 1979-07-02 12:00:00 blood 2767 #> 740 159.4 7 1979 1979-07-02 12:00:00 bone 2767 #> 741 142.2 8 1979 1979-08-01 22:00:00 blood 2768 #> 742 142.2 8 1979 1979-08-01 22:00:00 bone 2768 #> 743 188.4 9 1979 1979-09-01 08:00:00 blood 2769 #> 744 188.4 9 1979 1979-09-01 08:00:00 bone 2769 #> 745 186.2 10 1979 1979-10-01 18:00:00 blood 2770 #> 746 186.2 10 1979 1979-10-01 18:00:00 bone 2770 #> 747 183.3 11 1979 1979-11-01 04:00:00 blood 2771 #> 748 183.3 11 1979 1979-11-01 04:00:00 bone 2771 #> 749 176.3 12 1979 1979-12-01 14:00:00 blood 2772 #> 750 176.3 12 1979 1979-12-01 14:00:00 bone 2772 #> 751 159.6 1 1980 1980-01-01 00:00:00 blood 2773 #> 752 159.6 1 1980 1980-01-01 00:00:00 bone 2773 #> 753 155.0 2 1980 1980-01-31 12:00:00 blood 2774 #> 754 155.0 2 1980 1980-01-31 12:00:00 bone 2774 #> 755 126.2 3 1980 1980-03-02 00:00:00 blood 2775 #> 756 126.2 3 1980 1980-03-02 00:00:00 bone 2775 #> 757 164.1 4 1980 1980-04-01 12:00:00 blood 2776 #> 758 164.1 4 1980 1980-04-01 12:00:00 bone 2776 #> 759 179.9 5 1980 1980-05-02 00:00:00 blood 2777 #> 760 179.9 5 1980 1980-05-02 00:00:00 bone 2777 #> 761 157.3 6 1980 1980-06-01 12:00:00 blood 2778 #> 762 157.3 6 1980 1980-06-01 12:00:00 bone 2778 #> 763 136.3 7 1980 1980-07-02 00:00:00 blood 2779 #> 764 136.3 7 1980 1980-07-02 00:00:00 bone 2779 #> 765 135.4 8 1980 1980-08-01 12:00:00 blood 2780 #> 766 135.4 8 1980 1980-08-01 12:00:00 bone 2780 #> 767 155.0 9 1980 1980-09-01 00:00:00 blood 2781 #> 768 155.0 9 1980 1980-09-01 00:00:00 bone 2781 #> 769 164.7 10 1980 1980-10-01 12:00:00 blood 2782 #> 770 164.7 10 1980 1980-10-01 12:00:00 bone 2782 #> 771 147.9 11 1980 1980-11-01 00:00:00 blood 2783 #> 772 147.9 11 1980 1980-11-01 00:00:00 bone 2783 #> 773 174.4 12 1980 1980-12-01 12:00:00 blood 2784 #> 774 174.4 12 1980 1980-12-01 12:00:00 bone 2784 #> 775 114.0 1 1981 1981-01-01 00:00:00 blood 2785 #> 776 114.0 1 1981 1981-01-01 00:00:00 bone 2785 #> 777 141.3 2 1981 1981-01-31 10:00:00 blood 2786 #> 778 141.3 2 1981 1981-01-31 10:00:00 bone 2786 #> 779 135.5 3 1981 1981-03-02 20:00:00 blood 2787 #> 780 135.5 3 1981 1981-03-02 20:00:00 bone 2787 #> 781 156.4 4 1981 1981-04-02 06:00:00 blood 2788 #> 782 156.4 4 1981 1981-04-02 06:00:00 bone 2788 #> 783 127.5 5 1981 1981-05-02 16:00:00 blood 2789 #> 784 127.5 5 1981 1981-05-02 16:00:00 bone 2789 #> 785 90.0 6 1981 1981-06-02 02:00:00 blood 2790 #> 786 90.0 6 1981 1981-06-02 02:00:00 bone 2790 #> 787 143.8 7 1981 1981-07-02 12:00:00 blood 2791 #> 788 143.8 7 1981 1981-07-02 12:00:00 bone 2791 #> 789 158.7 8 1981 1981-08-01 22:00:00 blood 2792 #> 790 158.7 8 1981 1981-08-01 22:00:00 bone 2792 #> 791 167.3 9 1981 1981-09-01 08:00:00 blood 2793 #> 792 167.3 9 1981 1981-09-01 08:00:00 bone 2793 #> 793 162.4 10 1981 1981-10-01 18:00:00 blood 2794 #> 794 162.4 10 1981 1981-10-01 18:00:00 bone 2794 #> 795 137.5 11 1981 1981-11-01 04:00:00 blood 2795 #> 796 137.5 11 1981 1981-11-01 04:00:00 bone 2795 #> 797 150.1 12 1981 1981-12-01 14:00:00 blood 2796 #> 798 150.1 12 1981 1981-12-01 14:00:00 bone 2796 #> 799 111.2 1 1982 1982-01-01 00:00:00 blood 2797 #> 800 111.2 1 1982 1982-01-01 00:00:00 bone 2797 #> 801 163.6 2 1982 1982-01-31 10:00:00 blood 2798 #> 802 163.6 2 1982 1982-01-31 10:00:00 bone 2798 #> 803 153.8 3 1982 1982-03-02 20:00:00 blood 2799 #> 804 153.8 3 1982 1982-03-02 20:00:00 bone 2799 #> 805 122.0 4 1982 1982-04-02 06:00:00 blood 2800 #> 806 122.0 4 1982 1982-04-02 06:00:00 bone 2800 #> 807 82.2 5 1982 1982-05-02 16:00:00 blood 2801 #> 808 82.2 5 1982 1982-05-02 16:00:00 bone 2801 #> 809 110.4 6 1982 1982-06-02 02:00:00 blood 2802 #> 810 110.4 6 1982 1982-06-02 02:00:00 bone 2802 #> 811 106.1 7 1982 1982-07-02 12:00:00 blood 2803 #> 812 106.1 7 1982 1982-07-02 12:00:00 bone 2803 #> 813 107.6 8 1982 1982-08-01 22:00:00 blood 2804 #> 814 107.6 8 1982 1982-08-01 22:00:00 bone 2804 #> 815 118.8 9 1982 1982-09-01 08:00:00 blood 2805 #> 816 118.8 9 1982 1982-09-01 08:00:00 bone 2805 #> 817 94.7 10 1982 1982-10-01 18:00:00 blood 2806 #> 818 94.7 10 1982 1982-10-01 18:00:00 bone 2806 #> 819 98.1 11 1982 1982-11-01 04:00:00 blood 2807 #> 820 98.1 11 1982 1982-11-01 04:00:00 bone 2807 #> 821 127.0 12 1982 1982-12-01 14:00:00 blood 2808 #> 822 127.0 12 1982 1982-12-01 14:00:00 bone 2808 #> 823 84.3 1 1983 1983-01-01 00:00:00 blood 2809 #> 824 84.3 1 1983 1983-01-01 00:00:00 bone 2809 #> 825 51.0 2 1983 1983-01-31 10:00:00 blood 2810 #> 826 51.0 2 1983 1983-01-31 10:00:00 bone 2810 #> 827 66.5 3 1983 1983-03-02 20:00:00 blood 2811 #> 828 66.5 3 1983 1983-03-02 20:00:00 bone 2811 #> 829 80.7 4 1983 1983-04-02 06:00:00 blood 2812 #> 830 80.7 4 1983 1983-04-02 06:00:00 bone 2812 #> 831 99.2 5 1983 1983-05-02 16:00:00 blood 2813 #> 832 99.2 5 1983 1983-05-02 16:00:00 bone 2813 #> 833 91.1 6 1983 1983-06-02 02:00:00 blood 2814 #> 834 91.1 6 1983 1983-06-02 02:00:00 bone 2814 #> 835 82.2 7 1983 1983-07-02 12:00:00 blood 2815 #> 836 82.2 7 1983 1983-07-02 12:00:00 bone 2815 #> 837 71.8 8 1983 1983-08-01 22:00:00 blood 2816 #> 838 71.8 8 1983 1983-08-01 22:00:00 bone 2816 #> 839 50.3 9 1983 1983-09-01 08:00:00 blood 2817 #> 840 50.3 9 1983 1983-09-01 08:00:00 bone 2817 #> 841 55.8 10 1983 1983-10-01 18:00:00 blood 2818 #> 842 55.8 10 1983 1983-10-01 18:00:00 bone 2818 #> 843 33.3 11 1983 1983-11-01 04:00:00 blood 2819 #> 844 33.3 11 1983 1983-11-01 04:00:00 bone 2819 #> 845 33.4 12 1983 1983-12-01 14:00:00 blood 2820 #> 846 33.4 12 1983 1983-12-01 14:00:00 bone 2820 #> # An xts object example library(xts) #> Loading required package: zoo #> #> Attaching package: 'zoo' #> The following objects are masked from 'package:base': #> #> as.Date, as.Date.numeric dates <- seq(as.Date(\"2001-05-01\"), length=30, by=\"quarter\") data <- cbind(c(gas = rpois(30, cumprod(1+rnorm(30, mean = 0.01, sd = 0.001)))), c(oil = rpois(30, cumprod(1+rnorm(30, mean = 0.01, sd = 0.001))))) series <- xts(x = data, order.by = dates) colnames(series) <- c('gas', 'oil') head(series) #> gas oil #> 2001-05-01 2 2 #> 2001-08-01 1 1 #> 2001-11-01 1 2 #> 2002-02-01 1 3 #> 2002-05-01 4 1 #> 2002-08-01 1 3 series_to_mvgam(series, freq = 4, train_prop = 0.85) #> $data_train #> y season year date series time #> 1 2 2 2001 2001-05-01 gas 1 #> 2 2 2 2001 2001-05-01 oil 1 #> 3 1 3 2001 2001-08-01 gas 2 #> 4 1 3 2001 2001-08-01 oil 2 #> 5 1 4 2001 2001-11-01 gas 3 #> 6 2 4 2001 2001-11-01 oil 3 #> 7 1 1 2002 2002-02-01 gas 4 #> 8 3 1 2002 2002-02-01 oil 4 #> 9 4 2 2002 2002-05-01 gas 5 #> 10 1 2 2002 2002-05-01 oil 5 #> 11 1 3 2002 2002-08-01 gas 6 #> 12 3 3 2002 2002-08-01 oil 6 #> 13 0 4 2002 2002-11-01 gas 7 #> 14 1 4 2002 2002-11-01 oil 7 #> 15 0 1 2003 2003-02-01 gas 8 #> 16 2 1 2003 2003-02-01 oil 8 #> 17 3 2 2003 2003-05-01 gas 9 #> 18 3 2 2003 2003-05-01 oil 9 #> 19 0 3 2003 2003-08-01 gas 10 #> 20 0 3 2003 2003-08-01 oil 10 #> 21 1 4 2003 2003-11-01 gas 11 #> 22 0 4 2003 2003-11-01 oil 11 #> 23 2 1 2004 2004-02-01 gas 12 #> 24 0 1 2004 2004-02-01 oil 12 #> 25 1 2 2004 2004-05-01 gas 13 #> 26 1 2 2004 2004-05-01 oil 13 #> 27 0 3 2004 2004-08-01 gas 14 #> 28 2 3 2004 2004-08-01 oil 14 #> 29 0 4 2004 2004-11-01 gas 15 #> 30 2 4 2004 2004-11-01 oil 15 #> 31 0 1 2005 2005-02-01 gas 16 #> 32 1 1 2005 2005-02-01 oil 16 #> 33 1 2 2005 2005-05-01 gas 17 #> 34 2 2 2005 2005-05-01 oil 17 #> 35 0 3 2005 2005-08-01 gas 18 #> 36 0 3 2005 2005-08-01 oil 18 #> 37 1 4 2005 2005-11-01 gas 19 #> 38 0 4 2005 2005-11-01 oil 19 #> 39 1 1 2006 2006-02-01 gas 20 #> 40 0 1 2006 2006-02-01 oil 20 #> 41 1 2 2006 2006-05-01 gas 21 #> 42 4 2 2006 2006-05-01 oil 21 #> 43 0 3 2006 2006-08-01 gas 22 #> 44 0 3 2006 2006-08-01 oil 22 #> 45 0 4 2006 2006-11-01 gas 23 #> 46 1 4 2006 2006-11-01 oil 23 #> 47 1 1 2007 2007-02-01 gas 24 #> 48 2 1 2007 2007-02-01 oil 24 #> 49 1 2 2007 2007-05-01 gas 25 #> 50 0 2 2007 2007-05-01 oil 25 #> #> $data_test #> y season year date series time #> 1 0 3 2007 2007-08-01 gas 26 #> 2 3 3 2007 2007-08-01 oil 26 #> 3 3 4 2007 2007-11-01 gas 27 #> 4 2 4 2007 2007-11-01 oil 27 #> 5 0 1 2008 2008-02-01 gas 28 #> 6 1 1 2008 2008-02-01 oil 28 #> 7 0 2 2008 2008-05-01 gas 29 #> 8 1 2 2008 2008-05-01 oil 29 #> 9 0 3 2008 2008-08-01 gas 30 #> 10 3 3 2008 2008-08-01 oil 30 #>"},{"path":"https://nicholasjclark.github.io/mvgam/reference/sim_mvgam.html","id":null,"dir":"Reference","previous_headings":"","what":"Simulate a set of discrete time series for mvgam modelling — sim_mvgam","title":"Simulate a set of discrete time series for mvgam modelling — sim_mvgam","text":"function simulates discrete time series data fitting multivariate GAM includes shared seasonality dependence state-space latent dynamic factors. Random dependencies among series, .e. correlations long-term trends, included form correlated loadings latent dynamic factors","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/sim_mvgam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Simulate a set of discrete time series for mvgam modelling — sim_mvgam","text":"","code":"sim_mvgam( T = 100, n_series = 3, seasonality = \"shared\", use_lv = FALSE, n_lv = 1, trend_model = \"RW\", drift = FALSE, trend_rel = 0.2, freq = 12, family = poisson(), phi, shape, sigma, nu, mu, prop_missing = 0, train_prop = 0.85 )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/sim_mvgam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Simulate a set of discrete time series for mvgam modelling — sim_mvgam","text":"T integer. Number observations (timepoints) n_series integer. Number discrete time series seasonality character. Either shared, meaning series share exact seasonal pattern, hierarchical, meaning global seasonality series' pattern can deviate slightly use_lv logical. TRUE, use dynamic factors estimate series' latent trends reduced dimension format. FALSE, estimate independent latent trends series n_lv integer. Number latent dynamic factors generating series' trends trend_model character specifying time series dynamics latent trend. Options : None (latent trend component; .e. GAM component contributes linear predictor, observation process source error; similarly estimated gam) RW (random walk possible drift) AR1 (possible drift) AR2 (possible drift) AR3 (possible drift) VAR1 (contemporaneously uncorrelated VAR1) VAR1cor (contemporaneously correlated VAR1) GP (Gaussian Process squared exponential kernel) See mvgam_trends details drift logical, simulate drift term trend trend_rel numeric. Relative importance trend series. 0 1 freq integer. seasonal frequency series family family specifying exponential observation family series. Currently supported families : nb(), poisson(), tweedie(), gaussian(), betar(), lognormal(), student_t() Gamma() phi vector dispersion parameters series (.e. size Negative Binomial phi Tweedie Beta). length(phi) < n_series, first element phi replicated n_series times. Defaults 5 Negative Binomial Tweedie; 10 Beta shape vector shape parameters series (.e. shape Gamma) length(shape) < n_series, first element shape replicated n_series times. Defaults 10 sigma vector scale parameters series (.e. sd Normal Student-T, log(sd) LogNormal). length(sigma) < n_series, first element sigma replicated n_series times. Defaults 0.5 Normal Student-T; 0.2 Lognormal nu vector degrees freedom parameters series (.e. nu Student-T) length(nu) < n_series, first element nu replicated n_series times. Defaults 3 mu vector location parameters series. length(mu) < n_series, first element mu replicated n_series times. Defaults small random values -0.5 0.5 link scale prop_missing numeric stating proportion observations missing. 0 0.8, inclusive train_prop numeric stating proportion data use training. 0.25 0.75","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/sim_mvgam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Simulate a set of discrete time series for mvgam modelling — sim_mvgam","text":"list object containing outputs needed mvgam, including 'data_train' 'data_test', well additional information simulated seasonality trend dependencies","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/sim_mvgam.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Simulate a set of discrete time series for mvgam modelling — sim_mvgam","text":"","code":"#Simulate series with observations bounded at 0 and 1 (Beta responses) sim_data <- sim_mvgam(family = betar(), trend_model = 'GP', trend_rel = 0.6) plot_mvgam_series(data = sim_data$data_train, series = 'all') #Now simulate series with overdispersed discrete observations sim_data <- sim_mvgam(family = nb(), trend_model = 'GP', trend_rel = 0.6, phi = 10) plot_mvgam_series(data = sim_data$data_train, series = 'all')"},{"path":"https://nicholasjclark.github.io/mvgam/reference/summary.mvgam.html","id":null,"dir":"Reference","previous_headings":"","what":"Summary for a fitted mvgam object — summary.mvgam","title":"Summary for a fitted mvgam object — summary.mvgam","text":"functions take fitted mvgam object return various useful summaries","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/summary.mvgam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Summary for a fitted mvgam object — summary.mvgam","text":"","code":"# S3 method for mvgam summary(object, ...) # S3 method for mvgam_prefit summary(object, ...) # S3 method for mvgam coef(object, summarise = TRUE, ...)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/summary.mvgam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Summary for a fitted mvgam object — summary.mvgam","text":"object list object returned mvgam ... Ignored summarise logical. Summaries coefficients returned TRUE. Otherwise full posterior distribution returned","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/summary.mvgam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Summary for a fitted mvgam object — summary.mvgam","text":"summary.mvgam summary.mvgam_prefit, Aalist printed -screen showing summaries model coef.mvgam, either matrix posterior coefficient distributions (summarise == FALSE data.frame coefficient summaries)","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/summary.mvgam.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Summary for a fitted mvgam object — summary.mvgam","text":"summary.mvgam summary.mvgam_prefit return brief summaries model's call printed, along posterior intervals key parameters model. Note smooths extra penalties null space, summaries rho parameters may include penalty terms number smooths original model formula. coef.mvgam returns either summaries full posterior estimates GAM component coefficients","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/summary.mvgam.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Summary for a fitted mvgam object — summary.mvgam","text":"Nicholas J Clark","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/update.mvgam.html","id":null,"dir":"Reference","previous_headings":"","what":"Update an existing mvgam object — update.mvgam","title":"Update an existing mvgam object — update.mvgam","text":"function allows previously fitted mvgam model updated","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/update.mvgam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Update an existing mvgam object — update.mvgam","text":"","code":"# S3 method for mvgam update( object, formula, trend_formula, data, newdata, trend_model, trend_map, use_lv, n_lv, family, priors, ... )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/update.mvgam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Update an existing mvgam object — update.mvgam","text":"object fitted mvgam model formula Optional new formula object. Note, mvgam currently support dynamic formula updates removal specific terms - term. updating, entire formula needs supplied trend_formula optional character string specifying GAM process model formula. supplied, linear predictor modelled latent trends capture process model evolution separately observation model. response variable specified left-hand side formula (.e. valid option ~ season + s(year)). feature experimental, currently available Random Walk trend models. data dataframe list containing model response variable covariates required GAM formula. include columns: 'series' (character factor index series IDs) 'time' (numeric index time point observation). variables included linear predictor formula must also present newdata Optional dataframe list test data containing least 'series' 'time' addition variables included linear predictor formula. included, observations variable y set NA fitting model posterior simulations can obtained trend_model character specifying time series dynamics latent trend. Options : None (latent trend component; .e. GAM component contributes linear predictor, observation process source error; similarly estimated gam) RW (random walk possible drift) AR1 (possible drift) AR2 (possible drift) AR3 (possible drift) VAR1 (possible drift; available Stan) GP (Gaussian Process squared exponential kernel; available Stan) trend_map Optional data.frame specifying series depend latent trends. Useful allowing multiple series depend latent trend process, different observation processes. supplied, latent factor model set setting use_lv = TRUE using mapping set shared trends. Needs column names series trend, integer values trend column state trend series depend . series column single unique entry series data (names perfectly match factor levels series variable data). See examples mvgam details use_lv logical. TRUE, use dynamic factors estimate series' latent trends reduced dimension format. FALSE, estimate independent latent trends series n_lv integer number latent dynamic factors use use_lv == TRUE. >n_series. Defaults arbitrarily min(2, floor(n_series / 2)) family family specifying exponential observation family series. Currently supported families : nb(), poisson(), tweedie(), gaussian(), betar(), lognormal(), student_t() Gamma() priors optional data.frame prior definitions. See get_mvgam_priors mvgam information changing default prior distributions ... arguments passed mvgam","code":""}] +[{"path":"https://nicholasjclark.github.io/mvgam/authors.html","id":null,"dir":"","previous_headings":"","what":"Authors","title":"Authors and Citation","text":"Nicholas J Clark. Author, maintainer.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/authors.html","id":"citation","dir":"","previous_headings":"","what":"Citation","title":"Authors and Citation","text":"Nicholas J. Clark, Konstans Wells (2022). Dynamic Generalized Additive Models (DGAMs) forecasting discrete ecological time series Methods Ecology Evolution DOI: https://doi.org/10.1111/2041-210X.13974","code":"@Article{, title = {Dynamic Generalized Additive Models (DGAMs) for forecasting discrete ecological time series}, author = {Nicholas J. Clark and Konstans Wells}, journal = {Methods in Ecology and Evolution}, year = {2022}, url = {https://doi.org/10.1111/2041-210X.13974}, }"},{"path":"https://nicholasjclark.github.io/mvgam/index.html","id":"mvgam","dir":"","previous_headings":"","what":"mvgam","title":"Multivariate (Dynamic) Generalized Additive Models","text":"MultiVariate (Dynamic) Generalized Addivite Models goal mvgam use Bayesian framework estimate parameters Dynamic Generalized Additive Models (DGAMs) time series dynamic trend components. package provides interface fit Bayesian DGAMs using either JAGS Stan backend, note users strongly encouraged opt Stan JAGS. formula syntax based package mgcv provide familiar GAM modelling interface. motivation package primary objectives described detail Clark & Wells 2022 (published Methods Ecology Evolution).","code":""},{"path":"https://nicholasjclark.github.io/mvgam/index.html","id":"installation","dir":"","previous_headings":"","what":"Installation","title":"Multivariate (Dynamic) Generalized Additive Models","text":"Install development version GitHub using: devtools::install_github(\"nicholasjclark/mvgam\"). Note actually condition models MCMC sampling, either JAGS software must installed (along R packages rjags runjags) Stan software must installed (along either rstan /cmdstanr). rstan listed dependency mvgam ensure installation less difficult. users wish fit models using mvgam, please refer installation links JAGS , Stan rstan , Stan cmdstandr . need fairly recent version Stan ensure model syntax recognized. see warnings variable \"array\" exist, usually sign need update version Stan. highly recommend use Cmdstan cmdstanr interface backend. Cmdstan easier install, date new features, uses less memory Rstan. See documentation Cmdstan team information.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/index.html","id":"getting-started","dir":"","previous_headings":"","what":"Getting started","title":"Multivariate (Dynamic) Generalized Additive Models","text":"mvgam originally designed analyse forecast non-negative integer-valued data (counts). data traditionally challenging analyse existing time-series analysis packages. development mvgam resulted support growing number observation families extend types data. Currently, package can handle data following families: gaussian() real-valued data student_t() heavy-tailed real-valued data lognormal() non-negative real-valued data betar() proportional data (0,1) poisson() count data nb() overdispersed count data tweedie() overdispersed count data Note poisson(), nb(), tweedie() available using JAGS. families, apart tweedie(), supported using Stan. See ??mvgam_families information. simple example simulating modelling proportional data Beta observations set seasonal series independent Gaussian Process dynamic trends: Plot series see evolve time Fit DGAM series uses hierarchical cyclic seasonal smooth term capture variation seasonality among series. model also includes series-specific latent Gaussian Processes squared exponential covariance functions capture temporal dynamics Plot estimated posterior hindcast forecast distributions one series Various S3 functions can used inspect parameter estimates, plot smooth functions residuals, evaluate models posterior predictive checks forecast comparisons. Please see package documentation detailed examples.","code":"data <- sim_mvgam(family = betar(), T = 80, trend_model = 'GP', trend_rel = 0.5, seasonality = 'shared') plot_mvgam_series(data = data$data_train, series = 'all') mod <- mvgam(y ~ s(season, bs = 'cc', k = 7) + s(season, by = series, m = 1, k = 5), trend_model = 'GP', data = data$data_train, newdata = data$data_test, family = betar()) plot(mod, type = 'forecast', newdata = data$data_test, series = 2)"},{"path":"https://nicholasjclark.github.io/mvgam/index.html","id":"other-resources","dir":"","previous_headings":"","what":"Other resources","title":"Multivariate (Dynamic) Generalized Additive Models","text":"number case studies compiled highlight DGAMs can estimated using MCMC sampling. hosted currently RPubs following links: mvgam case study 1: model comparison data assimilation mvgam case study 2: multivariate models mvgam case study 3: distributed lag models package can also used generate necessary data structures, initial value functions modelling code necessary fit DGAMs using Stan JAGS. can helpful users wish make changes model better suit bespoke research / analysis goals. following resources can helpful troubleshoot: Stan Discourse JAGS Discourse","code":""},{"path":"https://nicholasjclark.github.io/mvgam/LICENSE.html","id":null,"dir":"","previous_headings":"","what":"MIT License","title":"MIT License","text":"Copyright (c) 2021 Nicholas Clark Permission hereby granted, free charge, person obtaining copy software associated documentation files (“Software”), deal Software without restriction, including without limitation rights use, copy, modify, merge, publish, distribute, sublicense, /sell copies Software, permit persons Software furnished , subject following conditions: copyright notice permission notice shall included copies substantial portions Software. SOFTWARE PROVIDED “”, WITHOUT WARRANTY KIND, EXPRESS IMPLIED, INCLUDING LIMITED WARRANTIES MERCHANTABILITY, FITNESS PARTICULAR PURPOSE NONINFRINGEMENT. EVENT SHALL AUTHORS COPYRIGHT HOLDERS LIABLE CLAIM, DAMAGES LIABILITY, WHETHER ACTION CONTRACT, TORT OTHERWISE, ARISING , CONNECTION SOFTWARE USE DEALINGS SOFTWARE.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/add_tweedie_lines.html","id":null,"dir":"Reference","previous_headings":"","what":"Tweedie JAGS modifications — add_tweedie_lines","title":"Tweedie JAGS modifications — add_tweedie_lines","text":"Tweedie JAGS modifications","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/add_tweedie_lines.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Tweedie JAGS modifications — add_tweedie_lines","text":"","code":"add_tweedie_lines(model_file, upper_bounds)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/add_tweedie_lines.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Tweedie JAGS modifications — add_tweedie_lines","text":"model_file template JAGS model file modified upper_bounds Optional upper bounds truncated observation likelihood","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/add_tweedie_lines.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Tweedie JAGS modifications — add_tweedie_lines","text":"modified JAGS model file","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/all_neon_tick_data.html","id":null,"dir":"Reference","previous_headings":"","what":"NEON Amblyomma and Ixodes tick abundance survey data — all_neon_tick_data","title":"NEON Amblyomma and Ixodes tick abundance survey data — all_neon_tick_data","text":"dataset containing timeseries Amblyomma americanum Ixodes scapularis nymph abundances NEON sites","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/all_neon_tick_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"NEON Amblyomma and Ixodes tick abundance survey data — all_neon_tick_data","text":"","code":"all_neon_tick_data"},{"path":"https://nicholasjclark.github.io/mvgam/reference/all_neon_tick_data.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"NEON Amblyomma and Ixodes tick abundance survey data — all_neon_tick_data","text":"tibble/dataframe containing covariate information alongside main fields : Year Year sampling epiWeek Epidemiological week sampling plot_ID NEON plot ID survey location siteID NEON site ID survey location amblyomma_americanum Counts . americanum nymphs ixodes_scapularis Counts . scapularis nymphs","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/all_neon_tick_data.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"NEON Amblyomma and Ixodes tick abundance survey data — all_neon_tick_data","text":"https://www.neonscience.org/data","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/code.html","id":null,"dir":"Reference","previous_headings":"","what":"Print the model code from an mvgam object — code","title":"Print the model code from an mvgam object — code","text":"Print model code mvgam object","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/code.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Print the model code from an mvgam object — code","text":"","code":"code(object)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/code.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Print the model code from an mvgam object — code","text":"object list object returned mvgam","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/code.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Print the model code from an mvgam object — code","text":"character string containing model code tidy format","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/dynamic.html","id":null,"dir":"Reference","previous_headings":"","what":"Defining dynamic coefficients in mvgam formulae — dynamic","title":"Defining dynamic coefficients in mvgam formulae — dynamic","text":"Set time-varying (dynamic) coefficients use mvgam models. Currently, low-rank Gaussian Process smooths available estimating dynamics time-varying coefficient.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/dynamic.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Defining dynamic coefficients in mvgam formulae — dynamic","text":"","code":"dynamic(variable, rho = 5, stationary = TRUE)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/dynamic.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Defining dynamic coefficients in mvgam formulae — dynamic","text":"variable variable dynamic smooth function rho Positive numeric stating length scale used approximating squared exponential Gaussian Process smooth. See gp.smooth details stationary logical. TRUE (default), latent Gaussian Process smooth linear trend component. FALSE, linear trend covariate added Gaussian Process smooth. Leave TRUE believe coefficient evolving much trend, linear component basis functions can hard penalize zero. sometimes causes divergence issues Stan. See gp.smooth details","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/dynamic.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Defining dynamic coefficients in mvgam formulae — dynamic","text":"mvgam currently sets dynamic coefficients low-rank squared exponential Gaussian Process smooths via call s(time, = variable, bs = \"gp\", m = c(2, rho, 2)). smooths, specified reasonable values length scale parameter, give realistic sample forecasts standard splines thin plate cubic. user must set value rho, currently support estimating value mgcv. may big problem, estimating latent length scales often difficult anyway. rho parameter thought prior smoothness latent dynamic coefficient function (higher values rho lead smoother functions temporal covariance structure. Values k set automatically ensure enough basis functions used approximate expected wiggliness underlying dynamic function (k increase rho decreases)","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/dynamic.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Defining dynamic coefficients in mvgam formulae — dynamic","text":"Nicholas J Clark","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/evaluate_mvgams.html","id":null,"dir":"Reference","previous_headings":"","what":"Evaluate forecasts from fitted mvgam objects — evaluate_mvgams","title":"Evaluate forecasts from fitted mvgam objects — evaluate_mvgams","text":"Evaluate forecasts fitted mvgam objects","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/evaluate_mvgams.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Evaluate forecasts from fitted mvgam objects — evaluate_mvgams","text":"","code":"eval_mvgam( object, n_samples = 5000, eval_timepoint = 3, fc_horizon = 3, n_cores = 2, score = \"drps\", log = FALSE, weights ) roll_eval_mvgam( object, n_evaluations = 5, evaluation_seq, n_samples = 5000, fc_horizon = 3, n_cores = 2, score = \"drps\", log = FALSE, weights ) compare_mvgams( model1, model2, n_samples = 1000, fc_horizon = 3, n_evaluations = 10, n_cores = 2, score = \"drps\", log = FALSE, weights )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/evaluate_mvgams.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Evaluate forecasts from fitted mvgam objects — evaluate_mvgams","text":"object list object returned mvgam n_samples integer specifying number samples generate model's posterior distribution eval_timepoint integer indexing timepoint represents last 'observed' set outcome data fc_horizon integer specifying length forecast horizon evaluating forecasts n_cores integer specifying number cores generating particle forecasts parallel score character specifying type ranked probability score use evaluation. Options : variogram, drps crps log logical. forecasts truths logged prior scoring? often appropriate comparing performance models series vary observation ranges weights optional vector weights (length(weights) == n_series) weighting pairwise correlations evaluating variogram score multivariate forecasts. Useful -weighting series larger magnitude observations less interest forecasting. Ignored score != 'variogram' n_evaluations integer specifying total number evaluations perform evaluation_seq Optional integer sequence specifying exact set timepoints evaluating model's forecasts. sequence values <3 > max(training timepoints) - fc_horizon model1 list object returned mvgam representing first model evaluated model2 list object returned mvgam representing second model evaluated","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/evaluate_mvgams.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Evaluate forecasts from fitted mvgam objects — evaluate_mvgams","text":"eval_mvgam, list object containing information specific evaluations series (using drps crps score) vector scores using variogram. roll_eval_mvgam, list object containing information specific evaluations series well total evaluation summary (taken summing forecast score series evaluation averaging coverages evaluation) compare_mvgams, series plots comparing forecast Rank Probability Scores competing model. lower score preferred. Note however possible select model ultimately perform poorly true --sample forecasting. example wiggly smooth function 'year' included model function learned prior evaluating rolling window forecasts, model generate tight predictions result. forecasting ahead timepoints model seen (.e. next year), smooth function end extrapolating, sometimes strange unexpected ways. therefore recommended use smooth functions covariates adequately measured data (.e. 'seasonality', example) reduce possible extrapolation smooths let latent trends mvgam model capture temporal dependencies data. trends time series models provide much stable forecasts","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/evaluate_mvgams.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Evaluate forecasts from fitted mvgam objects — evaluate_mvgams","text":"eval_mvgam generates set samples representing fixed parameters estimated full mvgam model latent trend states given point time. trends rolled forward total fc_horizon timesteps according estimated state space dynamics generate '--sample' forecast evaluated true observations horizon window. function therefore simulates situation model's parameters already estimated observed data evaluation timepoint like generate forecasts latent trends observed timepoint. Evaluation involves calculating appropriate Rank Probability Score binary indicator whether true value lies within forecast's 90% prediction interval roll_eval_mvgam sets sequence evaluation timepoints along rolling window iteratively calls eval_mvgam evaluate '--sample' forecasts. Evaluation involves calculating Discrete Rank Probability Score binary indicator whether true value lies within forecast's 90% prediction interval compare_mvgams automates evaluation compare two fitted models using rolling window forecast evaluation provides series summary plots facilitate model selection. essentially wrapper roll_eval_mvgam","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/forecast.mvgam.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract or compute hindcasts and forecasts for a fitted mvgam object — forecast.mvgam","title":"Extract or compute hindcasts and forecasts for a fitted mvgam object — forecast.mvgam","text":"Extract compute hindcasts forecasts fitted mvgam object","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/forecast.mvgam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract or compute hindcasts and forecasts for a fitted mvgam object — forecast.mvgam","text":"","code":"forecast(object, ...) # S3 method for mvgam forecast( object, newdata, data_test, series = \"all\", n_cores = 1, type = \"response\", ... )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/forecast.mvgam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract or compute hindcasts and forecasts for a fitted mvgam object — forecast.mvgam","text":"object list object returned mvgam. See mvgam() ... Ignored newdata Optional dataframe list test data containing least 'series' 'time' addition variables included linear predictor original formula. included, covariate information newdata used generate forecasts fitted model equations. newdata originally included call mvgam, forecasts already produced generative model simply extracted plotted. However newdata supplied original model call, assumption made newdata supplied comes sequentially data supplied data original model (.e. assume time gap last observation series 1 data first observation series 1 newdata) data_test Deprecated. Still works place newdata users recommended use newdata instead seamless integration R workflows series Either integer specifying series set forecast, character string '', specifying series forecast. preferable fitted model contained multivariate trends (either dynamic factor VAR process), saves recomputing full set trends series individually n_cores integer specifying number cores generating forecasts parallel type value link, linear predictor calculated log link scale. response used, predictions take uncertainty observation process account return predictions outcome (discrete) scale (default). trend used, forecast distribution latent trend returned","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/forecast.mvgam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extract or compute hindcasts and forecasts for a fitted mvgam object — forecast.mvgam","text":"object class mvgam_forecast containing hindcast forecast distributions. See mvgam_forecast-class details.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/forecast.mvgam.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Extract or compute hindcasts and forecasts for a fitted mvgam object — forecast.mvgam","text":"Posterior predictions drawn fitted mvgam used simulate forecast distribution","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/formula.mvgam.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract model.frame from a fitted mvgam object — formula.mvgam","title":"Extract model.frame from a fitted mvgam object — formula.mvgam","text":"Extract model.frame fitted mvgam object","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/formula.mvgam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract model.frame from a fitted mvgam object — formula.mvgam","text":"","code":"# S3 method for mvgam formula(x, trend_effects = FALSE, ...)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/formula.mvgam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract model.frame from a fitted mvgam object — formula.mvgam","text":"trend_effects logical, return model.frame observation model (FALSE) underlying process model (ifTRUE) ... Ignored","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/formula.mvgam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extract model.frame from a fitted mvgam object — formula.mvgam","text":"matrix containing fitted model frame","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/formula.mvgam.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Extract model.frame from a fitted mvgam object — formula.mvgam","text":"Nicholas J Clark","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/get_monitor_pars.html","id":null,"dir":"Reference","previous_headings":"","what":"Return parameters to monitor during modelling — get_monitor_pars","title":"Return parameters to monitor during modelling — get_monitor_pars","text":"Return parameters monitor modelling","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/get_monitor_pars.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Return parameters to monitor during modelling — get_monitor_pars","text":"","code":"get_monitor_pars(family, smooths_included = TRUE, use_lv, trend_model, drift)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/get_monitor_pars.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Return parameters to monitor during modelling — get_monitor_pars","text":"family character smooths_included Logical. smooth terms included model formula? use_lv Logical (use latent variable trends ) trend_model type trend model used drift Logical (drift term estimated )","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/get_monitor_pars.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Return parameters to monitor during modelling — get_monitor_pars","text":"string parameters monitor","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/get_mvgam_priors.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract information on default prior distributions for an mvgam model — get_mvgam_priors","title":"Extract information on default prior distributions for an mvgam model — get_mvgam_priors","text":"function lists parameters can prior distributions changed given mvgam model, well listing default distributions","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/get_mvgam_priors.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract information on default prior distributions for an mvgam model — get_mvgam_priors","text":"","code":"get_mvgam_priors( formula, trend_formula, data, data_train, family = \"poisson\", use_lv = FALSE, n_lv, use_stan = TRUE, trend_model = \"None\", trend_map, drift = FALSE )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/get_mvgam_priors.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract information on default prior distributions for an mvgam model — get_mvgam_priors","text":"formula character string specifying GAM formula. exactly like formula GLM except smooth terms, s, te, ti t2, can added right hand side specify linear predictor depends smooth functions predictors (linear functionals ) trend_formula optional character string specifying GAM process model formula. supplied, linear predictor modelled latent trends capture process model evolution separately observation model. response variable specified left-hand side formula (.e. valid option ~ season + s(year)). feature experimental, currently available Random Walk trend models. data dataframe list containing model response variable covariates required GAM formula. include columns: 'y' (discrete outcomes; NAs allowed) 'series' (character factor index series IDs) 'time' (numeric index time point observation). variables included linear predictor formula must also present data_train Deprecated. Still works place data users recommended use data instead seamless integration R workflows family family specifying exponential observation family series. Currently supported families : nb() count data poisson() count data tweedie() count data (power parameter p fixed 1.5) gaussian() real-valued data betar() proportional data (0,1) lognormal() non-negative real-valued data student_t() real-valued data Gamma() non-negative real-valued data See mvgam_families details use_lv logical. TRUE, use dynamic factors estimate series' latent trends reduced dimension format. FALSE, estimate independent latent trends series n_lv integer number latent dynamic factors use use_lv == TRUE. >n_series. Defaults arbitrarily min(2, floor(n_series / 2)) use_stan Logical. TRUE rstan installed, model compiled sampled using Hamiltonian Monte Carlo call cmdstan_model , cmdstanr available, call stan. Note functionality still development options available JAGS can used, including: option Tweedie family option dynamic factor trends. However, Stan can estimate Hilbert base approximate Gaussian Processes, much computationally tractable full GPs time series >100 observations, estimation Stan can support latent GP trends estimation JAGS trend_model character specifying time series dynamics latent trend. Options : None (latent trend component; .e. GAM component contributes linear predictor, observation process source error; similarly estimated gam) RW (random walk possible drift) AR1 (possible drift) AR2 (possible drift) AR3 (possible drift) VAR1 (contemporaneously uncorrelated VAR1; available Stan) VAR1cor (contemporaneously correlated VAR1; available Stan) GP (Gaussian Process squared exponential kernel; available Stan) See mvgam_trends details trend_map Optional data.frame specifying series depend latent trends. Useful allowing multiple series depend latent trend process, different observation processes. supplied, latent factor model set setting use_lv = TRUE using mapping set shared trends. Needs column names series trend, integer values trend column state trend series depend . series column single unique entry series data (names perfectly match factor levels series variable data). See examples mvgam details drift logical estimate drift parameter latent trend components. Useful latent trend expected broadly follow non-zero slope. Note latent trend less stationary, drift parameter can become unidentifiable, especially intercept term included GAM linear predictor (default calling jagam). Therefore defaults FALSE","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/get_mvgam_priors.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extract information on default prior distributions for an mvgam model — get_mvgam_priors","text":"either data.frame containing prior definitions (suitable priors can altered user) NULL, indicating priors model can modified mvgam interface","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/get_mvgam_priors.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Extract information on default prior distributions for an mvgam model — get_mvgam_priors","text":"Users can supply model formula, prior fitting model, default priors can inspected altered. make alterations, change contents prior column supplying data.frame mvgam function using argument priors. using Stan backend, users can also modify parameter bounds modifying new_lowerbound /new_upperbound columns. necessary using restrictive distributions parameters, Beta distribution trend sd parameters example (Beta support (0,1)), upperbound 1","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/get_mvgam_priors.html","id":"note","dir":"Reference","previous_headings":"","what":"Note","title":"Extract information on default prior distributions for an mvgam model — get_mvgam_priors","text":"prior, new_lowerbound /new_upperbound columns output altered defining user-defined priors mvgam model. Use familiar underlying probabilistic programming language. sanity checks done ensure code legal (.e. check lower bounds smaller upper bounds, example)","code":""},{"path":[]},{"path":"https://nicholasjclark.github.io/mvgam/reference/get_mvgam_priors.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Extract information on default prior distributions for an mvgam model — get_mvgam_priors","text":"Nicholas J Clark","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/get_mvgam_priors.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Extract information on default prior distributions for an mvgam model — get_mvgam_priors","text":"","code":"# Simulate three integer-valued time series library(mvgam) dat <- sim_mvgam(trend_rel = 0.5) # Get a model file that uses default mvgam priors for inspection (not always necessary, # but this can be useful for testing whether your updated priors are written correctly) mod_default <- mvgam(y ~ s(series, bs = 're') + s(season, bs = 'cc') - 1, family = 'nb', data = dat$data_train, trend_model = 'AR2', run_model = FALSE) # Inspect the model file with default mvgam priors mod_default$model_file #> [1] \"\" #> [2] \"// Stan model code generated by package mvgam\" #> [3] \"functions {\" #> [4] \"vector rep_each(vector x, int K) {\" #> [5] \"int N = rows(x);\" #> [6] \"vector[N * K] y;\" #> [7] \"int pos = 1;\" #> [8] \"for (n in 1:N) {\" #> [9] \"for (k in 1:K) {\" #> [10] \"y[pos] = x[n];\" #> [11] \"pos += 1;\" #> [12] \"}\" #> [13] \"}\" #> [14] \"return y;\" #> [15] \"}\" #> [16] \"}\" #> [17] \"data {\" #> [18] \"int total_obs; // total number of observations\" #> [19] \"int n; // number of timepoints per series\" #> [20] \"int n_sp; // number of smoothing parameters\" #> [21] \"int n_series; // number of series\" #> [22] \"int num_basis; // total number of basis coefficients\" #> [23] \"vector[num_basis] zero; // prior locations for basis coefficients\" #> [24] \"matrix[total_obs, num_basis] X; // mgcv GAM design matrix\" #> [25] \"int ytimes[n, n_series]; // time-ordered matrix (which col in X belongs to each [time, series] observation?)\" #> [26] \"matrix[8,8] S1; // mgcv smooth penalty matrix S1\" #> [27] \"int n_nonmissing; // number of nonmissing observations\" #> [28] \"int flat_ys[n_nonmissing]; // flattened nonmissing observations\" #> [29] \"matrix[n_nonmissing, num_basis] flat_xs; // X values for nonmissing observations\" #> [30] \"int obs_ind[n_nonmissing]; // indices of nonmissing observations\" #> [31] \"}\" #> [32] \"parameters {\" #> [33] \"// raw basis coefficients\" #> [34] \"vector[num_basis] b_raw;\" #> [35] \"\" #> [36] \"// random effect variances\" #> [37] \"vector[1] sigma_raw;\" #> [38] \"\" #> [39] \"// random effect means\" #> [40] \"vector[1] mu_raw;\" #> [41] \"\" #> [42] \"// negative binomial overdispersion\" #> [43] \"vector[n_series] phi_inv;\" #> [44] \"\" #> [45] \"// latent trend AR1 terms\" #> [46] \"vector[n_series] ar1;\" #> [47] \"\" #> [48] \"// latent trend AR2 terms\" #> [49] \"vector[n_series] ar2;\" #> [50] \"\" #> [51] \"// latent trend variance parameters\" #> [52] \"vector[n_series] sigma;\" #> [53] \"\" #> [54] \"// latent trends\" #> [55] \"matrix[n, n_series] trend;\" #> [56] \"\" #> [57] \"// smoothing parameters\" #> [58] \"vector[n_sp] lambda;\" #> [59] \"}\" #> [60] \"\" #> [61] \"transformed parameters {\" #> [62] \"// basis coefficients\" #> [63] \"vector[num_basis] b;\" #> [64] \"\" #> [65] \"b[1:8] = b_raw[1:8];\" #> [66] \"b[9:11] = mu_raw[1] + b_raw[9:11] * sigma_raw[1];\" #> [67] \"\" #> [68] \"}\" #> [69] \"\" #> [70] \"model {\" #> [71] \"// prior for random effect population variances\" #> [72] \"sigma_raw ~ exponential(0.5);\" #> [73] \"\" #> [74] \"// prior for random effect population means\" #> [75] \"mu_raw ~ std_normal();\" #> [76] \"\" #> [77] \"// prior for s(season)...\" #> [78] \"b_raw[1:8] ~ multi_normal_prec(zero[1:8],S1[1:8,1:8] * lambda[1]);\" #> [79] \"\" #> [80] \"// prior (non-centred) for s(series)...\" #> [81] \"b_raw[9:11] ~ std_normal();\" #> [82] \"\" #> [83] \"// priors for AR parameters\" #> [84] \"ar1 ~ std_normal();\" #> [85] \"ar2 ~ std_normal();\" #> [86] \"\" #> [87] \"// priors for smoothing parameters\" #> [88] \"lambda ~ normal(10, 25);\" #> [89] \"\" #> [90] \"// priors for overdispersion parameters\" #> [91] \"phi_inv ~ student_t(3, 0, 0.1);\" #> [92] \"\" #> [93] \"// priors for latent trend variance parameters\" #> [94] \"sigma ~ exponential(2);\" #> [95] \"\" #> [96] \"// trend estimates\" #> [97] \"trend[1, 1:n_series] ~ normal(0, sigma);\" #> [98] \"trend[2, 1:n_series] ~ normal(trend[1, 1:n_series] * ar1, sigma);\" #> [99] \"for(s in 1:n_series){\" #> [100] \"trend[3:n, s] ~ normal(ar1[s] * trend[2:(n - 1), s] + ar2[s] * trend[1:(n - 2), s], sigma[s]);\" #> [101] \"}\" #> [102] \"\" #> [103] \"{\" #> [104] \"// likelihood functions\" #> [105] \"vector[n_nonmissing] flat_trends;\" #> [106] \"real flat_phis[n_nonmissing];\" #> [107] \"flat_trends = (to_vector(trend))[obs_ind];\" #> [108] \"flat_phis = to_array_1d(rep_each(phi_inv, n)[obs_ind]);\" #> [109] \"flat_ys ~ neg_binomial_2(\" #> [110] \"exp(append_col(flat_xs, flat_trends) * append_row(b, 1.0)),\" #> [111] \"inv(flat_phis));\" #> [112] \"}\" #> [113] \"}\" #> [114] \"\" #> [115] \"generated quantities {\" #> [116] \"vector[total_obs] eta;\" #> [117] \"matrix[n, n_series] mus;\" #> [118] \"vector[n_sp] rho;\" #> [119] \"vector[n_series] tau;\" #> [120] \"array[n, n_series] int ypred;\" #> [121] \"matrix[n, n_series] phi_vec;\" #> [122] \"vector[n_series] phi;\" #> [123] \"phi = inv(phi_inv);\" #> [124] \"for (s in 1:n_series) {\" #> [125] \"phi_vec[1:n,s] = rep_vector(phi[s], n);\" #> [126] \"}\" #> [127] \"\" #> [128] \"rho = log(lambda);\" #> [129] \"for (s in 1:n_series) {\" #> [130] \"tau[s] = pow(sigma[s], -2.0);\" #> [131] \"}\" #> [132] \"\" #> [133] \"// posterior predictions\" #> [134] \"eta = X * b;\" #> [135] \"for(s in 1:n_series){ \" #> [136] \"mus[1:n, s] = eta[ytimes[1:n, s]] + trend[1:n, s];\" #> [137] \"ypred[1:n, s] = neg_binomial_2_rng(exp(mus[1:n, s]), phi_vec[1:n, s]);\" #> [138] \"}\" #> [139] \"}\" #> [140] \"\" # Look at which priors can be updated in mvgam test_priors <- get_mvgam_priors(y ~ s(series, bs = 're') + s(season, bs = 'cc') - 1, family = 'nb', data = dat$data_train, trend_model = 'AR2') test_priors #> param_name param_length #> 1 vector[n_sp] lambda; 2 #> 2 vector[1] mu_raw; 1 #> 3 vector[1] sigma_raw; 1 #> 4 vector[n_series] ar1; 3 #> 5 vector[n_series] ar2; 3 #> 6 vector[n_series] sigma; 3 #> 7 vector[n_series] phi_inv; 3 #> param_info prior #> 1 s(season) smooth parameters lambda ~ normal(10, 25); #> 2 s(series) pop mean mu_raw ~ std_normal(); #> 3 s(series) pop sd sigma_raw ~ exponential(0.5); #> 4 trend AR1 coefficient ar1 ~ std_normal(); #> 5 trend AR2 coefficient ar2 ~ std_normal(); #> 6 trend sd sigma ~ exponential(2); #> 7 inverse of NB dispsersion phi_inv ~ student_t(3, 0, 0.1); #> example_change new_lowerbound new_upperbound #> 1 lambda ~ exponential(0.23); NA NA #> 2 mu_raw ~ normal(-0.71, 0.93); NA NA #> 3 sigma_raw ~ exponential(0.78); NA NA #> 4 ar1 ~ normal(-0.23, 0.41); NA NA #> 5 ar2 ~ normal(0.98, 0.49); NA NA #> 6 sigma ~ exponential(0.81); NA NA #> 7 phi_inv ~ normal(-0.74, 0.88); NA NA # Make a few changes; first, change the population mean for the series-level # random intercepts test_priors$prior[2] <- 'mu_raw ~ normal(0.2, 0.5);' # Now use stronger regularisation for the series-level AR2 coefficients test_priors$prior[5] <- 'ar2 ~ normal(0, 0.25);' # Check that the changes are made to the model file without any warnings by # setting 'run_model = FALSE' mod <- mvgam(y ~ s(series, bs = 're') + s(season, bs = 'cc') - 1, family = 'nb', data = dat$data_train, trend_model = 'AR2', priors = test_priors, run_model = FALSE) code(mod) #> // Stan model code generated by package mvgam #> functions { #> vector rep_each(vector x, int K) { #> int N = rows(x); #> vector[N * K] y; #> int pos = 1; #> for (n in 1:N) { #> for (k in 1:K) { #> y[pos] = x[n]; #> pos += 1; #> } #> } #> return y; #> } #> } #> data { #> int total_obs; // total number of observations #> int n; // number of timepoints per series #> int n_sp; // number of smoothing parameters #> int n_series; // number of series #> int num_basis; // total number of basis coefficients #> vector[num_basis] zero; // prior locations for basis coefficients #> matrix[total_obs, num_basis] X; // mgcv GAM design matrix #> int ytimes[n, n_series]; // time-ordered matrix (which col in X belongs to each [time, series] observation?) #> matrix[8,8] S1; // mgcv smooth penalty matrix S1 #> int n_nonmissing; // number of nonmissing observations #> int flat_ys[n_nonmissing]; // flattened nonmissing observations #> matrix[n_nonmissing, num_basis] flat_xs; // X values for nonmissing observations #> int obs_ind[n_nonmissing]; // indices of nonmissing observations #> } #> parameters { #> // raw basis coefficients #> vector[num_basis] b_raw; #> // random effect variances #> vector[1] sigma_raw; #> // random effect means #> vector[1] mu_raw; #> // negative binomial overdispersion #> vector[n_series] phi_inv; #> // latent trend AR1 terms #> vector[n_series] ar1; #> // latent trend AR2 terms #> vector[n_series] ar2; #> // latent trend variance parameters #> vector[n_series] sigma; #> // latent trends #> matrix[n, n_series] trend; #> // smoothing parameters #> vector[n_sp] lambda; #> } #> transformed parameters { #> // basis coefficients #> vector[num_basis] b; #> b[1:8] = b_raw[1:8]; #> b[9:11] = mu_raw[1] + b_raw[9:11] * sigma_raw[1]; #> } #> model { #> // prior for random effect population variances #> sigma_raw ~ exponential(0.5); #> // prior for random effect population means #> mu_raw ~ normal(0.2, 0.5); #> // prior for s(season)... #> b_raw[1:8] ~ multi_normal_prec(zero[1:8],S1[1:8,1:8] * lambda[1]); #> // prior (non-centred) for s(series)... #> b_raw[9:11] ~ std_normal(); #> // priors for AR parameters #> ar1 ~ std_normal(); #> ar2 ~ normal(0, 0.25); #> // priors for smoothing parameters #> lambda ~ normal(10, 25); #> // priors for overdispersion parameters #> phi_inv ~ student_t(3, 0, 0.1); #> // priors for latent trend variance parameters #> sigma ~ exponential(2); #> // trend estimates #> trend[1, 1:n_series] ~ normal(0, sigma); #> trend[2, 1:n_series] ~ normal(trend[1, 1:n_series] * ar1, sigma); #> for(s in 1:n_series){ #> trend[3:n, s] ~ normal(ar1[s] * trend[2:(n - 1), s] + ar2[s] * trend[1:(n - 2), s], sigma[s]); #> } #> { #> // likelihood functions #> vector[n_nonmissing] flat_trends; #> real flat_phis[n_nonmissing]; #> flat_trends = (to_vector(trend))[obs_ind]; #> flat_phis = to_array_1d(rep_each(phi_inv, n)[obs_ind]); #> flat_ys ~ neg_binomial_2( #> exp(append_col(flat_xs, flat_trends) * append_row(b, 1.0)), #> inv(flat_phis)); #> } #> } #> generated quantities { #> vector[total_obs] eta; #> matrix[n, n_series] mus; #> vector[n_sp] rho; #> vector[n_series] tau; #> array[n, n_series] int ypred; #> matrix[n, n_series] phi_vec; #> vector[n_series] phi; #> phi = inv(phi_inv); #> for (s in 1:n_series) { #> phi_vec[1:n,s] = rep_vector(phi[s], n); #> } #> rho = log(lambda); #> for (s in 1:n_series) { #> tau[s] = pow(sigma[s], -2.0); #> } #> // posterior predictions #> eta = X * b; #> for(s in 1:n_series){ #> mus[1:n, s] = eta[ytimes[1:n, s]] + trend[1:n, s]; #> ypred[1:n, s] = neg_binomial_2_rng(exp(mus[1:n, s]), phi_vec[1:n, s]); #> } #> } # No warnings, the model is ready for fitting now in the usual way with the addition # of the 'priors' argument # Look at what is returned when an incorrect spelling is used test_priors$prior[5] <- 'ar2_bananas ~ normal(0, 0.25);' mod <- mvgam(y ~ s(series, bs = 're') + s(season, bs = 'cc') - 1, family = 'nb', data = dat$data_train, trend_model = 'AR2', priors = test_priors, run_model = FALSE) #> Warning: no match found in model_file for parameter: ar2_bananas code(mod) #> // Stan model code generated by package mvgam #> functions { #> vector rep_each(vector x, int K) { #> int N = rows(x); #> vector[N * K] y; #> int pos = 1; #> for (n in 1:N) { #> for (k in 1:K) { #> y[pos] = x[n]; #> pos += 1; #> } #> } #> return y; #> } #> } #> data { #> int total_obs; // total number of observations #> int n; // number of timepoints per series #> int n_sp; // number of smoothing parameters #> int n_series; // number of series #> int num_basis; // total number of basis coefficients #> vector[num_basis] zero; // prior locations for basis coefficients #> matrix[total_obs, num_basis] X; // mgcv GAM design matrix #> int ytimes[n, n_series]; // time-ordered matrix (which col in X belongs to each [time, series] observation?) #> matrix[8,8] S1; // mgcv smooth penalty matrix S1 #> int n_nonmissing; // number of nonmissing observations #> int flat_ys[n_nonmissing]; // flattened nonmissing observations #> matrix[n_nonmissing, num_basis] flat_xs; // X values for nonmissing observations #> int obs_ind[n_nonmissing]; // indices of nonmissing observations #> } #> parameters { #> // raw basis coefficients #> vector[num_basis] b_raw; #> // random effect variances #> vector[1] sigma_raw; #> // random effect means #> vector[1] mu_raw; #> // negative binomial overdispersion #> vector[n_series] phi_inv; #> // latent trend AR1 terms #> vector[n_series] ar1; #> // latent trend AR2 terms #> vector[n_series] ar2; #> // latent trend variance parameters #> vector[n_series] sigma; #> // latent trends #> matrix[n, n_series] trend; #> // smoothing parameters #> vector[n_sp] lambda; #> } #> transformed parameters { #> // basis coefficients #> vector[num_basis] b; #> b[1:8] = b_raw[1:8]; #> b[9:11] = mu_raw[1] + b_raw[9:11] * sigma_raw[1]; #> } #> model { #> // prior for random effect population variances #> sigma_raw ~ exponential(0.5); #> // prior for random effect population means #> mu_raw ~ normal(0.2, 0.5); #> // prior for s(season)... #> b_raw[1:8] ~ multi_normal_prec(zero[1:8],S1[1:8,1:8] * lambda[1]); #> // prior (non-centred) for s(series)... #> b_raw[9:11] ~ std_normal(); #> // priors for AR parameters #> ar1 ~ std_normal(); #> ar2 ~ std_normal(); #> // priors for smoothing parameters #> lambda ~ normal(10, 25); #> // priors for overdispersion parameters #> phi_inv ~ student_t(3, 0, 0.1); #> // priors for latent trend variance parameters #> sigma ~ exponential(2); #> // trend estimates #> trend[1, 1:n_series] ~ normal(0, sigma); #> trend[2, 1:n_series] ~ normal(trend[1, 1:n_series] * ar1, sigma); #> for(s in 1:n_series){ #> trend[3:n, s] ~ normal(ar1[s] * trend[2:(n - 1), s] + ar2[s] * trend[1:(n - 2), s], sigma[s]); #> } #> { #> // likelihood functions #> vector[n_nonmissing] flat_trends; #> real flat_phis[n_nonmissing]; #> flat_trends = (to_vector(trend))[obs_ind]; #> flat_phis = to_array_1d(rep_each(phi_inv, n)[obs_ind]); #> flat_ys ~ neg_binomial_2( #> exp(append_col(flat_xs, flat_trends) * append_row(b, 1.0)), #> inv(flat_phis)); #> } #> } #> generated quantities { #> vector[total_obs] eta; #> matrix[n, n_series] mus; #> vector[n_sp] rho; #> vector[n_series] tau; #> array[n, n_series] int ypred; #> matrix[n, n_series] phi_vec; #> vector[n_series] phi; #> phi = inv(phi_inv); #> for (s in 1:n_series) { #> phi_vec[1:n,s] = rep_vector(phi[s], n); #> } #> rho = log(lambda); #> for (s in 1:n_series) { #> tau[s] = pow(sigma[s], -2.0); #> } #> // posterior predictions #> eta = X * b; #> for(s in 1:n_series){ #> mus[1:n, s] = eta[ytimes[1:n, s]] + trend[1:n, s]; #> ypred[1:n, s] = neg_binomial_2_rng(exp(mus[1:n, s]), phi_vec[1:n, s]); #> } #> }"},{"path":"https://nicholasjclark.github.io/mvgam/reference/hindcast.mvgam.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract hindcasts for a fitted mvgam object — hindcast.mvgam","title":"Extract hindcasts for a fitted mvgam object — hindcast.mvgam","text":"Extract hindcasts fitted mvgam object","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/hindcast.mvgam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract hindcasts for a fitted mvgam object — hindcast.mvgam","text":"","code":"hindcast(object, ...) # S3 method for mvgam hindcast(object, series = \"all\", type = \"response\", ...)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/hindcast.mvgam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract hindcasts for a fitted mvgam object — hindcast.mvgam","text":"object list object returned mvgam. See mvgam() ... Ignored series Either integer specifying series set forecast, character string '', specifying series forecast. preferable fitted model contained multivariate trends (either dynamic factor VAR process), saves recomputing full set trends series individually type value link, linear predictor calculated log link scale. response used, predictions take uncertainty observation process account return predictions outcome (discrete) scale (default). trend used, hindcast distribution latent trend returned","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/hindcast.mvgam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extract hindcasts for a fitted mvgam object — hindcast.mvgam","text":"object class mvgam_forecast containing hindcast distributions. See mvgam_forecast-class details.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/hindcast.mvgam.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Extract hindcasts for a fitted mvgam object — hindcast.mvgam","text":"Posterior retrodictions drawn fitted mvgam organized convenient format","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/index-mvgam.html","id":null,"dir":"Reference","previous_headings":"","what":"Index mvgam objects — index-mvgam","title":"Index mvgam objects — index-mvgam","text":"Index mvgam objects","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/index-mvgam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Index mvgam objects — index-mvgam","text":"","code":"# S3 method for mvgam variables(x, ...)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/index-mvgam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Index mvgam objects — index-mvgam","text":"x list object class mvgam ... Arguments passed individual methods (applicable).","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/lfo_cv.mvgam.html","id":null,"dir":"Reference","previous_headings":"","what":"Approximate leave-future-out cross-validation of fitted mvgam objects — lfo_cv.mvgam","title":"Approximate leave-future-out cross-validation of fitted mvgam objects — lfo_cv.mvgam","text":"Approximate leave-future-cross-validation fitted mvgam objects","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/lfo_cv.mvgam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Approximate leave-future-out cross-validation of fitted mvgam objects — lfo_cv.mvgam","text":"","code":"lfo_cv(object, ...) # S3 method for mvgam lfo_cv( object, data, min_t, fc_horizon = 1, pareto_k_threshold = 0.7, n_cores = 1, ... )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/lfo_cv.mvgam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Approximate leave-future-out cross-validation of fitted mvgam objects — lfo_cv.mvgam","text":"object list object returned mvgam. See mvgam() ... Ignored data dataframe list containing model response variable covariates required GAM formula. include columns: 'series' (character factor index series IDs) 'time' (numeric index time point observation). variables included linear predictor formula must also present min_t Integer specifying minimum training time required making predictions data. Default either 30, whatever training time allows least 10 lfo-cv calculations (.e. pmin(max(data$time) - 10, 30)) fc_horizon Integer specifying number time steps ahead evaluating forecasts pareto_k_threshold Proportion specifying threshold Pareto shape parameter considered unstable, triggering model refit. Default 0.7 n_cores integer specifying number cores calculating likelihoods parallel","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/lfo_cv.mvgam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Approximate leave-future-out cross-validation of fitted mvgam objects — lfo_cv.mvgam","text":"list class mvgam_lfo containing approximate ELPD scores, Pareto-k shape values 'specified pareto_k_threshold","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/lfo_cv.mvgam.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Approximate leave-future-out cross-validation of fitted mvgam objects — lfo_cv.mvgam","text":"Approximate leave-future-cross-validation uses expanding training window scheme evaluate model forecasting ability. steps used function mirror laid lfo vignette loo package, written Paul Bürkner, Jonah Gabry, Aki Vehtari. First, refit model using first min_t observations perform single exact fc_horizon-ahead forecast step. forecast evaluated min_t + fc_horizon sample observations using Expected Log Predictive Density (ELPD). Next, approximate successive round expanding window forecasts moving forward one step time 1:N_evaluations re-weighting draws model's posterior predictive distribution using Pareto Smoothed Importance Sampling (PSIS). iteration , PSIS weights obtained next observation included model re-fit (.e. last observation training data, min_t + ). importance ratios stable, consider approximation adequate use re-weighted posterior's forecast evaluating next holdout set testing observations ((min_t + + 1):(min_t + + fc_horizon)). point importance ratio variability become large importance sampling fail. indicated estimated shape parameter k generalized Pareto distribution crossing certain threshold pareto_k_threshold. refit model using observations time failure. restart process iterate forward next refit triggered (Bürkner et al. 2020).","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/lfo_cv.mvgam.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Approximate leave-future-out cross-validation of fitted mvgam objects — lfo_cv.mvgam","text":"Paul-Christian Bürkner, Jonah Gabry & Aki Vehtari (2020). Approximate leave-future-cross-validation Bayesian time series models Journal Statistical Computation Simulation. 90:14, 2499-2523.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/lfo_cv.mvgam.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Approximate leave-future-out cross-validation of fitted mvgam objects — lfo_cv.mvgam","text":"Nicholas J Clark","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/logLik.mvgam.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute pointwise Log-Likelihoods from fitted mvgam objects — logLik.mvgam","title":"Compute pointwise Log-Likelihoods from fitted mvgam objects — logLik.mvgam","text":"Compute pointwise Log-Likelihoods fitted mvgam objects","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/logLik.mvgam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute pointwise Log-Likelihoods from fitted mvgam objects — logLik.mvgam","text":"","code":"# S3 method for mvgam logLik(object, n_cores = 1, ...)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/logLik.mvgam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute pointwise Log-Likelihoods from fitted mvgam objects — logLik.mvgam","text":"object list object returned mvgam n_cores integer specifying number cores calculating likelihoods parallel ... Ignored","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/logLik.mvgam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute pointwise Log-Likelihoods from fitted mvgam objects — logLik.mvgam","text":"matrix dimension n_samples x n_observations containing pointwise log-likelihood draws observations (training observations , supplied original model via newdata argument mvgam, testing observations)","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/lv_correlations.html","id":null,"dir":"Reference","previous_headings":"","what":"Calculate trend correlations based on mvgam latent factor loadings — lv_correlations","title":"Calculate trend correlations based on mvgam latent factor loadings — lv_correlations","text":"function uses samples latent trends series fitted mvgam model calculates correlations among series' trends","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/lv_correlations.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Calculate trend correlations based on mvgam latent factor loadings — lv_correlations","text":"","code":"lv_correlations(object)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/lv_correlations.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Calculate trend correlations based on mvgam latent factor loadings — lv_correlations","text":"object list object returned mvgam","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/lv_correlations.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Calculate trend correlations based on mvgam latent factor loadings — lv_correlations","text":"list object containing mean posterior correlations full array posterior correlations","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/model.frame.mvgam.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract model.frame from a fitted mvgam object — model.frame.mvgam","title":"Extract model.frame from a fitted mvgam object — model.frame.mvgam","text":"Extract model.frame fitted mvgam object","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/model.frame.mvgam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract model.frame from a fitted mvgam object — model.frame.mvgam","text":"","code":"# S3 method for mvgam model.frame(formula, trend_effects = FALSE, ...)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/model.frame.mvgam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract model.frame from a fitted mvgam object — model.frame.mvgam","text":"formula model formula terms object R object. trend_effects logical, return model.frame observation model (FALSE) underlying process model (ifTRUE) ... Ignored","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/model.frame.mvgam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extract model.frame from a fitted mvgam object — model.frame.mvgam","text":"matrix containing fitted model frame","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/model.frame.mvgam.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Extract model.frame from a fitted mvgam object — model.frame.mvgam","text":"Nicholas J Clark","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam-class.html","id":null,"dir":"Reference","previous_headings":"","what":"Fitted mvgam object description — mvgam-class","title":"Fitted mvgam object description — mvgam-class","text":"fitted mvgam object returned function mvgam. Run methods(class = \"mvgam\") see overview available methods.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam-class.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Fitted mvgam object description — mvgam-class","text":"mvgam object contains following elements: call original observation model formula trend_call trend_formula supplied, original trend model formula returned. Otherwise NULL family character description observation distribution trend_model character description latent trend model trend_map data.frame describing mapping trend states observations, supplied original model. Otherwise NULL drift Logical specifying whether drift term used trend model priors model priors updated defaults, prior dataframe returned. Otherwise NULL model_output MCMC object returned fitting engine. model fitted using Stan, object class stanfit (see stanfit-class details). JAGS used backend, object class runjags (see runjags-class details) model_file character string model file used describe model either Stan JAGS syntax model_data return_model_data set TRUE fitting model, list object containing data objects needed condition model returned. item list described detail top model_file. Otherwise NULL inits return_model_data set TRUE fitting model, initial value functions used initialise MCMC chains returned. Otherwise NULL monitor_pars parameters monitored MCMC sampling returned character vector sp_names character vector specifying names smoothing parameter mgcv_model object class gam containing mgcv version observation model. object used generating linear predictor matrix making predictions new data. coefficients model object contain posterior median coefficients GAM linear predictor, used generating plots smooth functions mvgam currently handle (plots three-dimensional smooths). model therefore used inference. See gamObject details trend_mgcv_model trend_formula supplied, object class gam containing mgcv version trend model. Otherwise NULL ytimes matrix object used model fitting indexing series timepoints observed row supplied data. Used internally downstream plotting prediction functions resids named list object containing posterior draws Dunn-Smyth randomized quantile residuals use_lv Logical flag indicating whether latent dynamic factors used model n_lv use_lv == TRUE, number latent dynamic factors used model upper_bounds bounds supplied original model fit, returned. Otherwise NULL obs_data original data object (either list dataframe) supplied model fitting. test_data test data supplied (argument newdata original model), returned. Othwerise NULL fit_engine Character describing fit engine, either stan jags max_treedepth model fitted using Stan, value supplied maximum treedepth tuning parameter returned (see stan details). Otherwise NULL adapt_delta model fitted using Stan, value supplied adapt_delta tuning parameter returned (see stan details). Otherwise NULL","code":""},{"path":[]},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam-class.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Fitted mvgam object description — mvgam-class","text":"Nicholas J Clark","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam.html","id":null,"dir":"Reference","previous_headings":"","what":"Fit a Bayesian dynamic GAM to a univariate or multivariate set of discrete time series — mvgam","title":"Fit a Bayesian dynamic GAM to a univariate or multivariate set of discrete time series — mvgam","text":"function estimates posterior distribution Generalised Additive Models (GAMs) can include smooth spline functions, specified GAM formula, well latent temporal processes, specified trend_model. currently two options specifying structures trends (either latent dynamic factors capture trend dependencies among series reduced dimension format, independent trends)","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Fit a Bayesian dynamic GAM to a univariate or multivariate set of discrete time series — mvgam","text":"","code":"mvgam( formula, trend_formula, knots, trend_knots, data, data_train, newdata, data_test, run_model = TRUE, prior_simulation = FALSE, return_model_data = FALSE, family = \"poisson\", use_lv = FALSE, n_lv, trend_map, trend_model = \"None\", drift = FALSE, chains = 4, burnin = 500, samples = 500, thin = 1, parallel = TRUE, threads = 1, priors, upper_bounds, refit = FALSE, use_stan = TRUE, max_treedepth, adapt_delta, jags_path )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Fit a Bayesian dynamic GAM to a univariate or multivariate set of discrete time series — mvgam","text":"formula character string specifying GAM observation model formula. exactly like formula GLM except smooth terms, s, te, ti t2, can added right hand side specify linear predictor depends smooth functions predictors (linear functionals ). trend_formula optional character string specifying GAM process model formula. supplied, linear predictor modelled latent trends capture process model evolution separately observation model. response variable specified left-hand side formula (.e. valid option ~ season + s(year)). feature experimental, currently available Random Walk trend models. knots optional list containing user specified knot values used basis construction. bases user simply supplies knots used, must match k value supplied (note number knots always just k). Different terms can use different numbers knots, unless share covariate. trend_knots knots , optional list knot values smooth functions within trend_formula data dataframe list containing model response variable covariates required GAM formula. include columns: series (character factor index series IDs) time (numeric index time point observation). variables included linear predictor formula must also present data_train Deprecated. Still works place data users recommended use data instead seamless integration R workflows newdata Optional dataframe list test data containing least 'series' 'time' addition variables included linear predictor formula. included, observations variable y set NA fitting model posterior simulations can obtained data_test Deprecated. Still works place newdata users recommended use newdata instead seamless integration R workflows run_model logical. FALSE, model fitted instead function return model file data / initial values needed fit model outside mvgam prior_simulation logical. TRUE, observations fed model, instead simulations prior distributions returned return_model_data logical. TRUE, list data needed fit model returned, along initial values smooth AR parameters, model fitted. helpful users wish modify model file add stochastic elements currently avaiable mvgam. Default FALSE reduce size returned object, unless run_model == FALSE family family specifying exponential observation family series. Currently supported families : nb() count data poisson() count data tweedie() count data (power parameter p fixed 1.5) gaussian() real-valued data betar() proportional data (0,1) lognormal() non-negative real-valued data student_t() real-valued data Gamma() non-negative real-valued data See mvgam_families details use_lv logical. TRUE, use dynamic factors estimate series' latent trends reduced dimension format. FALSE, estimate independent latent trends series n_lv integer number latent dynamic factors use use_lv == TRUE. >n_series. Defaults arbitrarily min(2, floor(n_series / 2)) trend_map Optional data.frame specifying series depend latent trends. Useful allowing multiple series depend latent trend process, different observation processes. supplied, latent factor model set setting use_lv = TRUE using mapping set shared trends. Needs column names series trend, integer values trend column state trend series depend . series column single unique entry series data (names perfectly match factor levels series variable data). See examples details trend_model character specifying time series dynamics latent trend. Options : None (latent trend component; .e. GAM component contributes linear predictor, observation process source error; similarly estimated gam) RW (random walk possible drift) AR1 (possible drift) AR2 (possible drift) AR3 (possible drift) VAR1 (contemporaneously uncorrelated VAR1; available Stan) VAR1cor (contemporaneously correlated VAR1; available Stan) GP (Gaussian Process squared exponential kernel; available Stan) See mvgam_trends details drift logical estimate drift parameter latent trend components. Useful latent trend expected broadly follow non-zero slope. Note latent trend less stationary, drift parameter can become unidentifiable, especially intercept term included GAM linear predictor (default calling jagam). Drift parameters also likely unidentifiable using dynamic factor models. Therefore defaults FALSE chains integer specifying number parallel chains model burnin integer specifying number warmup iterations Markov chain run tune sampling algorithms samples integer specifying number post-warmup iterations Markov chain run sampling posterior distribution thin Thinning interval monitors parallel logical specifying whether multiple cores used generating MCMC simulations parallel. TRUE, number cores use min(c(chains, parallel::detectCores() - 1)) threads integer Experimental option use multithreading within-chain parallelisation Stan. recommend use experienced Stan's reduce_sum function slow running model sped means. available using Cmdstan backend priors optional data.frame prior definitions (JAGS Stan syntax). See get_mvgam_priors 'Details' information changing default prior distributions upper_bounds Optional vector integer values specifying upper limits series. supplied, generates modified likelihood values bound given likelihood zero. Note modification computationally expensive JAGS can lead better estimates true bounds exist. Default remove truncation entirely (.e. upper bound series). Currently implemented Stan refit Logical indicating whether refit, called using update.mvgam. Users leave FALSE use_stan Logical. TRUE rstan installed, model compiled sampled using Hamiltonian Monte Carlo call cmdstan_model , cmdstanr available, call stan. Note many options using Stan vs JAGS (\"advantage\" JAGS ability use Tweedie family). max_treedepth positive integer placing cap number simulation steps evaluated iteration use_stan == TRUE. Default 12. Increasing value can sometimes help exploration complex posterior geometries, rarely fruitful go max_treedepth 14 adapt_delta positive numeric 0 1 defining target average proposal acceptance probability Stan's adaptation period, use_stan == TRUE. Default 0.8. general need change adapt_delta unless see warning message divergent transitions, case can increase adapt_delta default value closer 1 (e.g. 0.95 0.99, 0.99 0.999, etc). step size used numerical integrator function adapt_delta increasing adapt_delta result smaller step size fewer divergences. Increasing adapt_delta typically result slower sampler, always lead robust sampler. jags_path Optional character vector specifying path location JAGS executable (.exe) use modelling use_stan == FALSE. missing, path recovered call findjags","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Fit a Bayesian dynamic GAM to a univariate or multivariate set of discrete time series — mvgam","text":"list object class mvgam containing model output, text representation model file, mgcv model output (easily generating simulations unsampled covariate values), Dunn-Smyth residuals series key information needed functions package. See mvgam-class details.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Fit a Bayesian dynamic GAM to a univariate or multivariate set of discrete time series — mvgam","text":"Dynamic GAMs useful wish predict future values time series show temporal dependence want rely extrapolating smooth term (can sometimes lead unpredictable unrealistic behaviours). addition, smooths can often try wiggle excessively capture autocorrelation present time series, exacerbates problem forecasting ahead. GAMs naturally viewed Bayesian lens, often must model time series show complex distributional features missing data, parameters mvgam models estimated Bayesian framework using Markov Chain Monte Carlo. Priors: jagam model file generated formula modified include latent temporal processes. Prior distributions important model parameters can altered user inspect model sensitivities given priors (see get_mvgam_priors details). Note latent trends estimated log scale choose tau, AR phi priors accordingly. However control model specification can accomplished first using mvgam baseline, editing returned model accordingly. model file can edited run outside mvgam setting run_model = FALSE encouraged complex modelling tasks. Note, priors formally checked ensure right syntax respective probabilistic modelling framework, user ensure correct (.e. use dnorm normal densities JAGS, mean precision parameterisation; use normal normal densities Stan, mean standard deviation parameterisation) Random effects: smooth terms using random effect basis (smooth.construct.re.smooth.spec), non-centred parameterisation automatically employed avoid degeneracies common hierarchical models. Note however centred versions may perform better series particularly informative, foray Bayesian modelling, worth building understanding model's assumptions limitations following principled workflow. Also note models parameterised using drop.unused.levels = FALSE jagam ensure predictions can made levels supplied factor variable Overdispersion parameters: one series included data_train overdispersed exponential family used, additional observation family parameters (.e. phi nb() sigma gaussian()) estimated independently series. Factor regularisation: using dynamic factor model trends JAGS factor precisions given regularized penalty priors theoretically allow factors dropped model squeezing increasing factors' variances zero. done help protect selecting many latent factors needed capture dependencies data, can often advantageous set n_lv slightly larger number. However larger numbers factors come additional computational costs balanced well. using Stan, factors parameterised sd = 0.1 Residuals: series, randomized quantile (.e. Dunn-Smyth) residuals calculated inspecting model diagnostics fitted model appropriate Dunn-Smyth residuals standard normal distribution autocorrelation evident. particular observation missing, residual calculated comparing independent draws model's posterior distribution Using Stan: mvgam primarily designed use Hamiltonian Monte Carlo parameter estimation via software Stan (using either cmdstanr rstan interface). great advantages using Stan Gibbs / Metropolis Hastings samplers, includes option estimate smooth latent trends via Hilbert space approximate Gaussian Processes. often makes sense ecological series, expect change smoothly. mvgam, latent squared exponential GP trends approximated using default 40 basis functions, saves computational costs compared fitting full GPs adequately estimating GP alpha rho parameters. many advantages Stan JAGS, development package applied Stan. includes planned addition response distributions, plans handle zero-inflation, plans incorporate greater variety trend models. Users strongly encouraged opt Stan JAGS proceeding workflows","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Fit a Bayesian dynamic GAM to a univariate or multivariate set of discrete time series — mvgam","text":"Nicholas J Clark & Konstans Wells (2020). Dynamic generalised additive models (DGAMs) forecasting discrete ecological time series. Methods Ecology Evolution. 14:3, 771-784.","code":""},{"path":[]},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Fit a Bayesian dynamic GAM to a univariate or multivariate set of discrete time series — mvgam","text":"Nicholas J Clark","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Fit a Bayesian dynamic GAM to a univariate or multivariate set of discrete time series — mvgam","text":"","code":"if (FALSE) { # Simulate a collection of three time series that have shared seasonal dynamics dat <- sim_mvgam(T = 80, n_series = 3, prop_missing = 0.1, trend_rel = 0.6) # Plot key summary statistics for a single series plot_mvgam_series(data = dat$data_train, series = 1) # Plot all series together plot_mvgam_series(data = dat$data_train, series = 'all') # Formulate a model using Stan where series share a cyclic smooth for # seasonality and each series has an independent random walk temporal process; # Set run_model = FALSE to inspect the returned objects mod1 <- mvgam(formula = y ~ s(season, bs = 'cc'), data = dat$data_train, trend_model = 'RW', family = 'poisson', use_stan = TRUE, run_model = FALSE) # View the model code in Stan language code(mod1) # Inspect the data objects needed to condition the model str(mod1$model_data) # Inspect the initial value function used to initialise the MCMC chains mod1$inits # The following code can be used to run the model outside of mvgam; first using rstan model_data <- mod1$model_data library(rstan) fit <- stan(model_code = mod1$model_file, data = model_data, init = mod1$inits) # Now using cmdstanr library(cmdstanr) model_data <- mod1$model_data cmd_mod <- cmdstan_model(write_stan_file(mod1$model_file), stanc_options = list('canonicalize=deprecations,braces,parentheses')) cmd_mod$print() fit <- cmd_mod$sample(data = model_data, chains = 4, parallel_chains = 4, refresh = 100, init = mod1$inits) # Now fit the model using mvgam with the Stan backend mod1 <- mvgam(formula = y ~ s(season, bs = 'cc'), data = dat$data_train, trend_model = 'RW', family = poisson(), use_stan = TRUE) # Extract the model summary summary(mod1) # Plot the estimated historical trend and forecast for one series plot(mod1, type = 'trend', series = 1) plot(mod1, type = 'forecast', series = 1) # Compute the forecast using covariate information in data_test plot(object = mod1, type = 'trend', newdata = dat$data_test, series = 1) plot(object = mod1, type = 'forecast', newdata = dat$data_test, series = 1) # Plot the estimated seasonal smooth function plot(mod1, type = 'smooths') # Plot estimated first derivatives of the smooth plot(mod1, type = 'smooths', derivatives = TRUE) # Plot partial residuals of the smooth plot(mod1, type = 'smooths', residuals = TRUE) # Plot posterior realisations for the smooth plot(mod1, type = 'smooths', realisations = TRUE) # Extract observation model beta coefficient draws as a data.frame beta_draws_df <- as.data.frame(mod1, variable = 'betas') head(beta_draws_df) str(beta_draws_df) # Example of supplying a trend_map so that some series can share # latent trend processes sim <- sim_mvgam(n_series = 3) mod_data <- sim$data_train # Here, we specify only two latent trends; series 1 and 2 share a trend, # while series 3 has it's own unique latent trend trend_map <- data.frame(series = unique(mod_data$series), trend = c(1,1,2)) # Fit the model using AR1 trends mod1 <- mvgam(y ~ s(season, bs = 'cc'), trend_map = trend_map, trend_model = 'AR1', data = mod_data, return_model_data = TRUE) # The mapping matrix is now supplied as data to the model in the 'Z' element mod1$model_data$Z code(mod1) # The first two series share an identical latent trend; the third is different plot(mod1, type = 'trend', series = 1) plot(mod1, type = 'trend', series = 2) plot(mod1, type = 'trend', series = 3) # Example of how to use dynamic coefficients # Simulate a time-varying coefficient for the effect of temperature set.seed(3) N = 200 beta_temp <- vector(length = N) beta_temp[1] <- 0.4 for(i in 2:N){ beta_temp[i] <- rnorm(1, mean = beta_temp[i - 1], sd = 0.025) } # Simulate the temperature covariate temp <- rnorm(N, sd = 1) # Simulate the Gaussian observation process out <- rnorm(N, mean = 4 + beta_temp * temp, sd = 0.5) # Gather necessary data into a data.frame; split into training / testing data = data.frame(out, temp, time = seq_along(temp)) data_train <- data[1:180,] data_test <- data[181:200,] # Fit the model using the dynamic() formula helper mod <- mvgam(formula = out ~ dynamic(temp, rho = 8), family = gaussian(), data = data_train, newdata = data_test) # Inspect the model summary, forecast and time-varying coefficient distribution summary(mod) plot(mod, type = 'smooths') plot(mod, type = 'forecast', newdata = data_test) # Propagating the smooth term shows how the coefficient is expected to evolve plot_mvgam_smooth(mod, smooth = 1, newdata = data) abline(v = 180, lty = 'dashed', lwd = 2) # Example showing how to incorporate an offset; simulate some count data # with different means per series set.seed(100) dat <- sim_mvgam(trend_rel = 0, mu = c(0, 2, 2), seasonality = 'hierarchical') # Add offset terms to the training and testing data dat$data_train$offset <- 0.5 * as.numeric(dat$data_train$series) dat$data_test$offset <- 0.5 * as.numeric(dat$data_test$series) # Fit a model that includes the offset in the linear predictor as well as # hierarchical seasonal smooths mod1 <- mvgam(formula = y ~ offset(offset) + s(series, bs = 're') + s(season, bs = 'cc') + s(season, by = series, m = 1, k = 5), data = dat$data_train, trend_model = 'None', use_stan = TRUE) # Inspect the model file to see the modification to the linear predictor # (eta) mod1$model_file # Forecasts for the first two series will differ in magnitude layout(matrix(1:2, ncol = 2)) plot(mod1, type = 'forecast', series = 1, newdata = dat$data_test, ylim = c(0, 75)) plot(mod1, type = 'forecast', series = 2, newdata = dat$data_test, ylim = c(0, 75)) layout(1) # Changing the offset for the testing data should lead to changes in # the forecast dat$data_test$offset <- dat$data_test$offset - 2 plot(mod1, 'forecast', newdata = dat$data_test) # Relative Risks can be computed by fixing the offset to the same value # for each series dat$data_test$offset <- rep(1, NROW(dat$data_test)) preds_rr <- predict(mod1, type = 'link', newdata = dat$data_test) series1_inds <- which(dat$data_test$series == 'series_1') series2_inds <- which(dat$data_test$series == 'series_2') # Relative Risks are now more comparable among series layout(matrix(1:2, ncol = 2)) plot(preds_rr[1, series1_inds], type = 'l', col = 'grey75', ylim = range(preds_rr), ylab = 'Series1 Relative Risk', xlab = 'Time') for(i in 2:50){ lines(preds_rr[i, series1_inds], col = 'grey75') } plot(preds_rr[1, series2_inds], type = 'l', col = 'darkred', ylim = range(preds_rr), ylab = 'Series2 Relative Risk', xlab = 'Time') for(i in 2:50){ lines(preds_rr[i, series2_inds], col = 'darkred') } layout(1) }"},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_draws.html","id":null,"dir":"Reference","previous_headings":"","what":"Extract posterior draws from fitted mvgam objects — mvgam_draws","title":"Extract posterior draws from fitted mvgam objects — mvgam_draws","text":"Extract posterior draws conventional formats data.frames, matrices, arrays.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_draws.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Extract posterior draws from fitted mvgam objects — mvgam_draws","text":"","code":"# S3 method for mvgam as.data.frame( x, row.names = NULL, optional = TRUE, variable = \"betas\", regex = FALSE, ... ) # S3 method for mvgam as.matrix(x, variable = \"betas\", regex = FALSE, ...)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_draws.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Extract posterior draws from fitted mvgam objects — mvgam_draws","text":"x list object class mvgam row.names Ignored optional Ignored variable character specifying parameters extract. Can either one following options: obs_params (parameters specific observation model, overdispsersions negative binomial models observation error SD gaussian / student-t models) betas (beta coefficients GAM observation model linear predictor; default) smooth_params (smoothing parameters GAM observation model) linpreds (estimated linear predictors whatever link scale used model) trend_params (parameters governing trend dynamics, AR parameters, trend SD parameters Gaussian Process parameters) trend_betas (beta coefficients GAM latent process model linear predictor; available trend_formula supplied original model) trend_smooth_params (process model GAM smoothing parameters; available trend_formula supplied original model) trend_linpreds (process model linear predictors identity scale; available trend_formula supplied original model) can character vector providing variables extract regex Logical. using one prespecified options extractions, variable treated (vector ) regular expressions? variable x matching least one regular expressions selected. Defaults FALSE. ... Ignored","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_draws.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Extract posterior draws from fitted mvgam objects — mvgam_draws","text":"data.frame, matrix, array containing posterior draws.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_draws.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Extract posterior draws from fitted mvgam objects — mvgam_draws","text":"","code":"if (FALSE) { sim <- sim_mvgam(family = Gamma()) mod1 <- mvgam(y ~ s(season, bs = 'cc'), trend_model = 'AR1', data = sim$data_train, family = Gamma()) beta_draws_df <- as.data.frame(mod1, variable = 'betas') head(beta_draws_df) str(beta_draws_df) beta_draws_mat <- as.data.frame(mod1, variable = 'betas') head(beta_draws_mat) str(beta_draws_mat)}"},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_families.html","id":null,"dir":"Reference","previous_headings":"","what":"Supported mvgam families — mvgam_families","title":"Supported mvgam families — mvgam_families","text":"Supported mvgam families","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_families.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Supported mvgam families — mvgam_families","text":"","code":"tweedie(link = \"log\") student_t(link = \"identity\")"},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_families.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Supported mvgam families — mvgam_families","text":"link specification family link function. present changed","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_families.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Supported mvgam families — mvgam_families","text":"mvgam currently supports following standard observation families: gaussian real-valued data poisson count data Gamma non-negative real-valued data addition, following extended families mgcv package supported: betar proportional data (0,1) nb count data Finally, mvgam supports three extended families described : lognormal non-negative real-valued data tweedie count data (power parameter p fixed 1.5) student-t real-valued data Note poisson(), nb(), tweedie() available using JAGS. families, apart tweedie(), supported using Stan.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_families.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Supported mvgam families — mvgam_families","text":"Nicholas J Clark","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_forecast-class.html","id":null,"dir":"Reference","previous_headings":"","what":"mvgam_forecast object description — mvgam_forecast-class","title":"mvgam_forecast object description — mvgam_forecast-class","text":"mvgam_forecast object returned function hindcast forecast. Run methods(class = \"mvgam_forecast\") see overview available methods.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_forecast-class.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"mvgam_forecast object description — mvgam_forecast-class","text":"mvgam_forecast object contains following elements: call original observation model formula trend_call trend_formula supplied, original trend model formula returned. Otherwise NULL family character description observation distribution trend_model character description latent trend model drift Logical specifying whether drift term used trend model use_lv Logical flag indicating whether latent dynamic factors used model fit_engine Character describing fit engine, either stan jags type type predictions included (either link, response trend) series_names Names time series, taken levels(data$series) original model fit train_observations list training observation vectors length n_series test_observations forecast function used, list test observation vectors length n_series. Otherwise NULL hindcasts list posterior hindcast distributions length n_series. forecasts forecast function used, list posterior forecast distributions length n_series. Otherwise NULL","code":""},{"path":[]},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_forecast-class.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"mvgam_forecast object description — mvgam_forecast-class","text":"Nicholas J Clark","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_marginaleffects.html","id":null,"dir":"Reference","previous_headings":"","what":"Helper functions for mvgam marginaleffects calculations — mvgam_marginaleffects","title":"Helper functions for mvgam marginaleffects calculations — mvgam_marginaleffects","text":"Helper functions mvgam marginaleffects calculations Functions needed working marginaleffects Functions needed getting data / objects insight","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_marginaleffects.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Helper functions for mvgam marginaleffects calculations — mvgam_marginaleffects","text":"","code":"# S3 method for mvgam get_coef(model, trend_effects = FALSE, ...) # S3 method for mvgam set_coef(model, coefs, trend_effects = FALSE, ...) # S3 method for mvgam get_vcov(model, vcov = NULL, ...) # S3 method for mvgam get_predict( model, newdata, type = \"response\", process_error = FALSE, n_cores = 1, ... ) # S3 method for mvgam get_data(x, source = \"environment\", verbose = TRUE, ...) # S3 method for mvgam find_predictors( x, effects = c(\"fixed\", \"random\", \"all\"), component = c(\"all\", \"conditional\", \"zi\", \"zero_inflated\", \"dispersion\", \"instruments\", \"correlation\", \"smooth_terms\"), flatten = FALSE, verbose = TRUE, ... )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_marginaleffects.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Helper functions for mvgam marginaleffects calculations — mvgam_marginaleffects","text":"model Model object ... Additional arguments passed predict() method supplied modeling package.arguments particularly useful mixed-effects bayesian models (see online vignettes marginaleffects website). Available arguments can vary model model, depending range supported arguments modeling package. See \"Model-Specific Arguments\" section ?marginaleffects documentation non-exhaustive list available arguments. coefs vector coefficients insert model object vcov Type uncertainty estimates report (e.g., robust standard errors). Acceptable values: FALSE: compute standard errors. can speed computation considerably. TRUE: Unit-level standard errors using default vcov(model) variance-covariance matrix. String indicates kind uncertainty estimates return. Heteroskedasticity-consistent: \"HC\", \"HC0\", \"HC1\", \"HC2\", \"HC3\", \"HC4\", \"HC4m\", \"HC5\". See ?sandwich::vcovHC Heteroskedasticity autocorrelation consistent: \"HAC\" Mixed-Models degrees freedom: \"satterthwaite\", \"kenward-roger\" : \"NeweyWest\", \"KernHAC\", \"OPG\". See sandwich package documentation. One-sided formula indicates name cluster variables (e.g., ~unit_id). formula passed cluster argument sandwich::vcovCL function. Square covariance matrix Function returns covariance matrix (e.g., stats::vcov(model)) newdata Grid predictor values evaluate slopes. NULL (default): Unit-level slopes observed value original dataset. See insight::get_data() data frame: Unit-level slopes row newdata data frame. datagrid() call specify custom grid regressors. example: newdata = datagrid(cyl = c(4, 6)): cyl variable equal 4 6 regressors fixed means modes. See Examples section datagrid() documentation. string: \"mean\": Marginal Effects Mean. Slopes predictor held mean mode. \"median\": Marginal Effects Median. Slopes predictor held median mode. \"marginalmeans\": Marginal Effects Marginal Means. See Details section . \"tukey\": Marginal Effects Tukey's 5 numbers. \"grid\": Marginal Effects grid representative numbers (Tukey's 5 numbers unique values categorical predictors). type string indicates type (scale) predictions used compute contrasts slopes. can differ based model type, typically string : \"response\", \"link\", \"probs\", \"zero\". unsupported string entered, model-specific list acceptable values returned error message. type NULL, default value used. default first model-related row marginaleffects:::type_dictionary dataframe. process_error logical. TRUE, uncertainty latent process (trend) model incorporated predictions n_cores Integer specifying number cores use generating predictions x fitted model. source String, indicating data recovered. source = \"environment\" (default), data recovered environment (e.g. data workspace). option usually fastest way getting data ensures original variables used model fitting returned. Note always current data recovered environment. Hence, data modified model fitting (e.g., variables recoded rows filtered), returned data may longer equal model data. source = \"frame\" (\"mf\"), data taken model frame. transformed variables back-transformed, possible. option returns data even available environment, however, certain edge cases back-transforming original data may fail. source = \"environment\" fails recover data, tries extract data model frame; source = \"frame\" data extracted model frame, data recovered environment. ways returns observations missing data variables used model fitting. verbose Toggle messages warnings. effects model data fixed effects (\"fixed\"), random effects (\"random\") (\"\") returned? applies mixed gee models. component predictor variables, predictor variables conditional model, zero-inflated part model, dispersion term instrumental variables returned? Applies models zero-inflated /dispersion formula, models instrumental variable (called fixed-effects regressions). May abbreviated. Note conditional component also called count mean component, depending model. flatten Logical, TRUE, values returned character vector, list. Duplicated values removed.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_marginaleffects.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Helper functions for mvgam marginaleffects calculations — mvgam_marginaleffects","text":"Nicholas J Clark","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_trends.html","id":null,"dir":"Reference","previous_headings":"","what":"Supported mvgam trend models — mvgam_trends","title":"Supported mvgam trend models — mvgam_trends","text":"Supported mvgam trend models","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_trends.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Supported mvgam trend models — mvgam_trends","text":"mvgam currently supports following dynamic trend models: RW Random Walk AR1 Autoregressive model AR coefficient lag 1 AR2 Autoregressive model AR coefficients lags 1 2 AR3 Autoregressive model AR coefficients lags 1, 2 3 VAR1 Vector Autoregressive model VAR coefficients lag 1; contemporaneously uncorrelated process errors VAR1cor Vector Autoregressive model VAR coefficients lag 1; contemporaneously correlated process errors GP Squared exponential Gaussian Process None latent trend fitted Dynamic factor models can used latent factors evolve either RW, AR1, AR2, AR3 GP. Note RW, AR1, AR2 AR3 available using JAGS. trend models supported using Stan. multivariate trend models (.e. VAR VARcor models), users can either fix trend error covariances 0 (using VAR) estimate potentially allow contemporaneously correlated errors using VARcor. VAR models, stationarity latent process enforced prior using parameterisation given Heaps (2022). Stationarity enforced using AR1, AR2 AR3 models, though can changed user specifying lower upper bounds autoregressive parameters using functionality get_mvgam_priors priors argument mvgam","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/mvgam_trends.html","id":"references","dir":"Reference","previous_headings":"","what":"References","title":"Supported mvgam trend models — mvgam_trends","text":"Sarah E. Heaps (2022) Enforcing stationarity prior Vector Autoregressions. Journal Computational Graphical Statistics. 32:1, 1-10.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/pfilter_mvgam_fc.html","id":null,"dir":"Reference","previous_headings":"","what":"Forecast from a particle filtered mvgam object — pfilter_mvgam_fc","title":"Forecast from a particle filtered mvgam object — pfilter_mvgam_fc","text":"function generates forecast set particles capture unique proposal current state system modelled mvgam object. covariate timepoint information data_test used generate GAM component forecast, trends run forward time according state space dynamics. forecast weighted ensemble, weights determined particle's proposal likelihood prior recent assimilation step","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/pfilter_mvgam_fc.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Forecast from a particle filtered mvgam object — pfilter_mvgam_fc","text":"","code":"pfilter_mvgam_fc( file_path = \"pfilter\", n_cores = 2, newdata, data_test, plot_legend = TRUE, legend_position = \"topleft\", ylim, return_forecasts = FALSE )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/pfilter_mvgam_fc.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Forecast from a particle filtered mvgam object — pfilter_mvgam_fc","text":"file_path character string specifying file path particles saved n_cores integer specifying number cores generating particle forecasts parallel newdata dataframe list test data containing least 'series' time', addition variables included linear predictor formula data_test Deprecated. Still works place newdata users recommended use newdata instead seamless integration R workflows plot_legend logical stating whether include legend highlight observations used calibration assimilated particle filter legend_position legend location may specified setting x single keyword list \"bottomright\", \"bottom\", \"bottomleft\", \"left\", \"topleft\", \"top\", \"topright\", \"right\" \"center\". places legend inside plot frame given location. ylim Optional vector y-axis limits (min, max). limits used plots return_forecasts logical. TRUE, returned list object contain plots forecasts well forecast objects (matrix dimension n_particles x horizon)","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/pfilter_mvgam_fc.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Forecast from a particle filtered mvgam object — pfilter_mvgam_fc","text":"named list containing functions call base R plots series' forecast. Optionally actual forecasts returned within list separate list matrices","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/pfilter_mvgam_init.html","id":null,"dir":"Reference","previous_headings":"","what":"Initiate particles for online filtering from a fitted mvgam object — pfilter_mvgam_init","title":"Initiate particles for online filtering from a fitted mvgam object — pfilter_mvgam_init","text":"function generates set particles captures unique proposal current state system. next observation data_assim assimilated particles weighted proposal's multivariate composite likelihood update model's forecast distribution","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/pfilter_mvgam_init.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Initiate particles for online filtering from a fitted mvgam object — pfilter_mvgam_init","text":"","code":"pfilter_mvgam_init( object, newdata, data_assim, n_particles = 1000, file_path = \"pfilter\", n_cores = 2 )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/pfilter_mvgam_init.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Initiate particles for online filtering from a fitted mvgam object — pfilter_mvgam_init","text":"object list object returned mvgam newdata dataframe list test data containing least one observation per series (beyond last observation seen model object) assimilated particle filter. least contain 'series' 'time' one-step ahead horizon, addition variables included linear predictor object data_assim Deprecated. Still works place newdata users recommended use newdata instead seamless integration R workflows n_particles integer specifying number unique particles generate tracking latent system state file_path character string specifying file path saving initiated particles n_cores integer specifying number cores generating particle forecasts parallel","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/pfilter_mvgam_init.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Initiate particles for online filtering from a fitted mvgam object — pfilter_mvgam_init","text":"list object length = n_particles containing information parameters current state estimates particle generated saved, along important information original model, .rda object file_path","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/pfilter_mvgam_online.html","id":null,"dir":"Reference","previous_headings":"","what":"Automatic online particle filtering for assimilating new observations into a fitted mvgam model — pfilter_mvgam_online","title":"Automatic online particle filtering for assimilating new observations into a fitted mvgam model — pfilter_mvgam_online","text":"function operates sequentially new observations data_assim update posterior forecast distribution. wrapper calls pfilter_mvgam_smooth. iteration, next observation assimilated particles weighted proposal's multivariate composite likelihood","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/pfilter_mvgam_online.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Automatic online particle filtering for assimilating new observations into a fitted mvgam model — pfilter_mvgam_online","text":"","code":"pfilter_mvgam_online( newdata, data_assim, file_path = \"pfilter\", threshold = 0.5, use_resampling = FALSE, kernel_lambda = 0.25, n_cores = 1 )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/pfilter_mvgam_online.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Automatic online particle filtering for assimilating new observations into a fitted mvgam model — pfilter_mvgam_online","text":"newdata dataframe list test data containing least one observation per series (beyond last observation seen model initialising particles pfilter_mvgam_init previous calls pfilter_mvgam_online. least contain 'series' 'time' one-step ahead horizon, addition variables included linear predictor object data_assim Deprecated. Still works place newdata users recommended use newdata instead seamless integration R workflows file_path character string specifying file path locating particles threshold proportional numeric specifying Effective Sample Size limit resampling particles triggered (calculated ESS / n_particles) use_resampling == TRUE. 0 1 use_resampling logical specifying whether resampling used ESS falls specified threshold. Default option FALSE, relying instead kernel smoothing maintain particle diversity kernel_lambda proportional numeric specifying strength kernel smoothing use pulling low weight particles toward high likelihood state space. 0 1 n_cores integer specifying number cores generating particle forecasts parallel","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/pfilter_mvgam_online.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Automatic online particle filtering for assimilating new observations into a fitted mvgam model — pfilter_mvgam_online","text":"list object length = n_particles containing information parameters current state estimates particle generated saved, along important information original model, .rda object file_path","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/pfilter_mvgam_smooth.html","id":null,"dir":"Reference","previous_headings":"","what":"Assimilate new observations into a fitted mvgam model using resampling and kernel smoothing — pfilter_mvgam_smooth","title":"Assimilate new observations into a fitted mvgam model using resampling and kernel smoothing — pfilter_mvgam_smooth","text":"function operates new observation next_assim update posterior forecast distribution. next observation assimilated particle weights updated light recent multivariate composite likelihood. Low weight particles smoothed towards high weight state space using importance sampling, options given using resampling high weight particles Effective Sample Size falls user-specified threshold","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/pfilter_mvgam_smooth.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Assimilate new observations into a fitted mvgam model using resampling and kernel smoothing — pfilter_mvgam_smooth","text":"","code":"pfilter_mvgam_smooth( particles, mgcv_model, next_assim, threshold = 0.25, n_cores = 1, use_resampling = FALSE, kernel_lambda = 0.5 )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/pfilter_mvgam_smooth.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Assimilate new observations into a fitted mvgam model using resampling and kernel smoothing — pfilter_mvgam_smooth","text":"particles list particles run one observation prior observation next_assim mgcv_model gam model returned call link{mvgam} next_assim dataframe test data containing one observation per series (beyond last observation seen model initialising particles pfilter_mvgam_init previous calls pfilter_mvgam_online. least contain 'series' 'time' one-step ahead horizon, addition variables included linear predictor object threshold proportional numeric specifying Effective Sample Size limit resampling particles triggered (calculated ESS / n_particles) use_resampling == TRUE. 0 1 n_cores integer specifying number cores generating particle forecasts parallel use_resampling logical specifying whether resampling used ESS falls specified threshold. Note resampling can result loss original model's diversity GAM beta coefficients, may undesirable consequences forecast distribution. use_resampling TRUE, effort made remedy assigning randomly sampled draws GAM beta coefficients original model's distribution particle. however guarantee loss diversity, especially successive resampling take place. Default option therefore FALSE kernel_lambda proportional numeric specifying strength smoothing use pulling low weight particles toward high likelihood state space. 0 1","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/pfilter_mvgam_smooth.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Assimilate new observations into a fitted mvgam model using resampling and kernel smoothing — pfilter_mvgam_smooth","text":"list object length = n_particles containing information parameters current state estimates particle","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/pipe.html","id":null,"dir":"Reference","previous_headings":"","what":"Pipe operator — %>%","title":"Pipe operator — %>%","text":"See magrittr::%>% details.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/pipe.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Pipe operator — %>%","text":"","code":"lhs %>% rhs"},{"path":"https://nicholasjclark.github.io/mvgam/reference/pipe.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Pipe operator — %>%","text":"lhs value magrittr placeholder. rhs function call using magrittr semantics.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/pipe.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Pipe operator — %>%","text":"result calling rhs(lhs).","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot.mvgam.html","id":null,"dir":"Reference","previous_headings":"","what":"Default mvgam plots — plot.mvgam","title":"Default mvgam plots — plot.mvgam","text":"function takes fitted mvgam object produces plots smooth functions, forecasts, trends uncertainty components","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot.mvgam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Default mvgam plots — plot.mvgam","text":"","code":"# S3 method for mvgam plot( x, type = \"residuals\", series = 1, residuals = FALSE, newdata, data_test, trend_effects = FALSE, ... )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot.mvgam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Default mvgam plots — plot.mvgam","text":"x list object returned mvgam. See mvgam() type character specifying type plot return. Options : 'series, residuals, smooths, re (random effect smooths), pterms (parametric effects), forecast, trend, uncertainty, factors series integer specifying series set plotted. ignored type == 're' residuals logical. TRUE type = residuals, posterior quantiles partial residuals added plots 1-D smooths series ribbon rectangles. Partial residuals smooth term median Dunn-Smyth residuals obtained dropping term concerned model, leaving estimates fixed (.e. estimates term plus original median Dunn-Smyth residuals). Note mvgam works Dunn-Smyth residuals working residuals, used mgcv, magnitudes partial residuals different expect plot.gam. Interpretation similar though, partial residuals evenly scattered around smooth function function well estimated newdata Optional dataframe list test data containing least 'series' 'time' addition variables included linear predictor original formula. argument optional plotting sample forecast period observations (type = forecast) required plotting uncertainty components (type = uncertainty). data_test Deprecated. Still works place newdata users recommended use newdata instead seamless integration R workflows trend_effects logical. TRUE trend_formula used model fitting, terms trend (.e. process) model plotted ... Additional arguments individual plotting function.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot.mvgam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Default mvgam plots — plot.mvgam","text":"base R plot set plots","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot.mvgam.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Default mvgam plots — plot.mvgam","text":"plots useful getting overview fitted model estimated random effects smooth functions, individual plotting functions generally offer customisation.","code":""},{"path":[]},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot.mvgam.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Default mvgam plots — plot.mvgam","text":"Nicholas J Clark","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot.mvgam_lfo.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot Pareto-k and ELPD values from a leave-future-out object — plot.mvgam_lfo","title":"Plot Pareto-k and ELPD values from a leave-future-out object — plot.mvgam_lfo","text":"function takes object class mvgam_lfo create several informative diagnostic plots","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot.mvgam_lfo.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot Pareto-k and ELPD values from a leave-future-out object — plot.mvgam_lfo","text":"","code":"# S3 method for mvgam_lfo plot(x, ...)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot.mvgam_lfo.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot Pareto-k and ELPD values from a leave-future-out object — plot.mvgam_lfo","text":"x object class mvgam_lfo ... Ignored","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot.mvgam_lfo.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot Pareto-k and ELPD values from a leave-future-out object — plot.mvgam_lfo","text":"base R plot Pareto-k ELPD values evaluation timepoints. Pareto-k plot, dashed red line indicates specified threshold chosen triggering model refits. ELPD plot, dashed red line indicated bottom 10% quantile ELPD values. Points threshold may represent outliers difficult forecast","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_factors.html","id":null,"dir":"Reference","previous_headings":"","what":"Latent factor summaries for a fitted mvgam object — plot_mvgam_factors","title":"Latent factor summaries for a fitted mvgam object — plot_mvgam_factors","text":"function takes fitted mvgam object returns plots summary statistics latent dynamic factors","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_factors.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Latent factor summaries for a fitted mvgam object — plot_mvgam_factors","text":"","code":"plot_mvgam_factors(object, plot = TRUE)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_factors.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Latent factor summaries for a fitted mvgam object — plot_mvgam_factors","text":"object list object returned mvgam plot logical specifying whether factors plotted","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_factors.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Latent factor summaries for a fitted mvgam object — plot_mvgam_factors","text":"dataframe factor contributions , optionally, series base R plots","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_factors.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Latent factor summaries for a fitted mvgam object — plot_mvgam_factors","text":"model object estimated using dynamic factors, possible factors contributed estimated trends. due regularisation penalty acts independently factor's Gaussian precision, squeeze un-needed factors white noise process (effectively dropping factor model). function, factor tested null hypothesis white noise calculating sum factor's 2nd derivatives. factor larger contribution larger sum due weaker penalty factor's precision. plot == TRUE, factors also plotted.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_factors.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Latent factor summaries for a fitted mvgam object — plot_mvgam_factors","text":"Nicholas J Clark","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_forecasts.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot mvgam posterior predictions for a specified series — plot_mvgam_forecasts","title":"Plot mvgam posterior predictions for a specified series — plot_mvgam_forecasts","text":"Plot mvgam posterior predictions specified series","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_forecasts.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot mvgam posterior predictions for a specified series — plot_mvgam_forecasts","text":"","code":"plot_mvgam_fc( object, series = 1, newdata, data_test, realisations = FALSE, n_realisations = 15, hide_xlabels = FALSE, xlab, ylab, ylim, n_cores = 1, return_forecasts = FALSE, return_score = FALSE, ... ) # S3 method for mvgam_forecast plot( x, series = 1, realisations = FALSE, n_realisations = 15, hide_xlabels = FALSE, xlab, ylab, ylim, return_score = FALSE, ... )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_forecasts.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot mvgam posterior predictions for a specified series — plot_mvgam_forecasts","text":"object list object returned mvgam series integer specifying series set plotted newdata Optional dataframe list test data containing least 'series' 'time' addition variables included linear predictor original formula. included, covariate information newdata used generate forecasts fitted model equations. newdata originally included call mvgam, forecasts already produced generative model simply extracted plotted. However newdata supplied original model call, assumption made newdata supplied comes sequentially data supplied data original model (.e. assume time gap last observation series 1 data first observation series 1 newdata). newdata contains observations column y, observations used compute Discrete Rank Probability Score forecast distribution data_test Deprecated. Still works place newdata users recommended use newdata instead seamless integration R workflows realisations logical. TRUE, forecast realisations shown spaghetti plot, making easier visualise diversity possible forecasts. FALSE, default, empirical quantiles forecast distribution shown n_realisations integer specifying number posterior realisations plot, realisations = TRUE. Ignored otherwise hide_xlabels logical. TRUE, xlabels printed allow user add custom labels using axis base R xlab label x axis. ylab label y axis. ylim Optional vector y-axis limits (min, max) n_cores integer specifying number cores generating forecasts parallel return_forecasts logical. TRUE, function plot forecast well returning forecast object (matrix dimension n_samples x horizon) return_score logical. TRUE sample test data provided newdata, probabilistic score calculated returned. score used depend observation family fitted model. Discrete families (poisson, negative binomial, tweedie) use Discrete Rank Probability Score. families use Continuous Rank Probability Score. value returned sum scores within sample forecast horizon ... par graphical parameters. x Object class mvgam_forecast","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_forecasts.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot mvgam posterior predictions for a specified series — plot_mvgam_forecasts","text":"base R graphics plot optional list containing forecast distribution sample probabilistic forecast score","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_forecasts.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot mvgam posterior predictions for a specified series — plot_mvgam_forecasts","text":"plot_mvgam_fc draws posterior predictions object class mvgam calculates posterior empirical quantiles. plot.mvgam_forecast takes object class mvgam_forecast, forecasts already computed, plots resulting forecast distribution. realisations = FALSE, posterior quantiles plotted along true observed data used train model. Otherwise, spaghetti plot returned show possible forecast paths.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_pterms.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot mvgam parametric term partial effects — plot_mvgam_pterms","title":"Plot mvgam parametric term partial effects — plot_mvgam_pterms","text":"function plots posterior empirical quantiles partial effects parametric terms","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_pterms.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot mvgam parametric term partial effects — plot_mvgam_pterms","text":"","code":"plot_mvgam_pterms(object, trend_effects = FALSE)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_pterms.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot mvgam parametric term partial effects — plot_mvgam_pterms","text":"object list object returned mvgam trend_effects logical. TRUE trend_formula used model fitting, terms trend (.e. process) model plotted","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_pterms.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot mvgam parametric term partial effects — plot_mvgam_pterms","text":"base R graphics plot","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_pterms.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot mvgam parametric term partial effects — plot_mvgam_pterms","text":"Posterior empirical quantiles parametric term's partial effect estimates (link scale) calculated visualised ribbon plots. effects can interpreted partial effect parametric term contributes terms model set 0","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_randomeffects.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot mvgam random effect terms — plot_mvgam_randomeffects","title":"Plot mvgam random effect terms — plot_mvgam_randomeffects","text":"function plots posterior empirical quantiles random effect smooths (bs = re)","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_randomeffects.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot mvgam random effect terms — plot_mvgam_randomeffects","text":"","code":"plot_mvgam_randomeffects(object, trend_effects = FALSE)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_randomeffects.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot mvgam random effect terms — plot_mvgam_randomeffects","text":"object list object returned mvgam trend_effects logical. TRUE trend_formula used model fitting, terms trend (.e. process) model plotted","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_randomeffects.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot mvgam random effect terms — plot_mvgam_randomeffects","text":"base R graphics plot","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_randomeffects.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot mvgam random effect terms — plot_mvgam_randomeffects","text":"Posterior empirical quantiles random effect coefficient estimates (link scale) calculated visualised ribbon plots. Labels coefficients taken levels original factor variable used specify smooth model's formula","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_resids.html","id":null,"dir":"Reference","previous_headings":"","what":"Residual diagnostics for a fitted mvgam object — plot_mvgam_resids","title":"Residual diagnostics for a fitted mvgam object — plot_mvgam_resids","text":"function takes fitted mvgam object returns various residual diagnostic plots","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_resids.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Residual diagnostics for a fitted mvgam object — plot_mvgam_resids","text":"","code":"plot_mvgam_resids(object, series = 1, n_bins = 15, newdata, data_test)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_resids.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Residual diagnostics for a fitted mvgam object — plot_mvgam_resids","text":"object list object returned mvgam series integer specifying series set plotted n_bins integer specifying number bins use binning fitted values newdata Optional dataframe list test data containing least 'series', 'y', 'time' addition variables included linear predictor formula. included, covariate information newdata used generate forecasts fitted model equations. newdata originally included call mvgam, forecasts already produced generative model simply extracted used calculate residuals. However newdata supplied original model call, assumption made newdata supplied comes sequentially data supplied data original model (.e. assume time gap last observation series 1 data_train first observation series 1 newdata). data_test Deprecated. Still works place newdata users recommended use newdata instead seamless integration R workflows","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_resids.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Residual diagnostics for a fitted mvgam object — plot_mvgam_resids","text":"series base R plots","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_resids.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Residual diagnostics for a fitted mvgam object — plot_mvgam_resids","text":"total four base R plots generated examine Dunn-Smyth residuals specified series. Plots include residuals vs fitted values plot, Q-Q plot, two plots check remaining temporal autocorrelation residuals. Note, plots use posterior medians fitted values / residuals, uncertainty represented.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_resids.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Residual diagnostics for a fitted mvgam object — plot_mvgam_resids","text":"Nicholas J Clark","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_series.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot observed time series used for mvgam modelling — plot_mvgam_series","title":"Plot observed time series used for mvgam modelling — plot_mvgam_series","text":"function takes either fitted mvgam object data_train object produces plots observed time series, ACF, CDF histograms exploratory data analysis","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_series.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot observed time series used for mvgam modelling — plot_mvgam_series","text":"","code":"plot_mvgam_series( object, data, data_train, newdata, data_test, y = \"y\", lines = TRUE, series = 1, n_bins, log_scale = FALSE )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_series.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot observed time series used for mvgam modelling — plot_mvgam_series","text":"object Optional list object returned mvgam. Either object data_train must supplied. data Optional dataframe list training data containing least 'series' 'time'. Use argument training data gathered correct format mvgam modelling model yet fitted. data_train Deprecated. Still works place data users recommended use data instead seamless integration R workflows newdata Optional dataframe list test data containing least 'series' 'time' forecast horizon, addition variables included linear predictor formula. included, observed values test data compared model's forecast distribution exploring biases model predictions. data_test Deprecated. Still works place newdata users recommended use newdata instead seamless integration R workflows y Character. name outcome variable supplied data? Defaults 'y' lines Logical. TRUE, line plots used visualising time series. FALSE, points used. series Either integer specifying series set plotted string '', plots series available supplied data n_bins integer specifying number bins use binning observed values plotting histogram. Default use number bins returned call hist base R log_scale logical. series == '', flag used control whether time series plot shown log scale (using log(Y + 1)). can useful visualising many series may different observed ranges. Default FALSE","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_series.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot observed time series used for mvgam modelling — plot_mvgam_series","text":"set base R graphics plots. series integer, plots show observed time series, autocorrelation cumulative distribution functions, histogram series. series == '', set observed time series plots returned series shown plot single focal series highlighted, remaining series shown faint gray lines.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_series.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Plot observed time series used for mvgam modelling — plot_mvgam_series","text":"Nicholas J Clark","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_smooth.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot mvgam smooth terms — plot_mvgam_smooth","title":"Plot mvgam smooth terms — plot_mvgam_smooth","text":"function plots posterior empirical quantiles series-specific smooth term","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_smooth.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot mvgam smooth terms — plot_mvgam_smooth","text":"","code":"plot_mvgam_smooth( object, trend_effects = FALSE, series = 1, smooth, residuals = FALSE, n_resid_bins = 25, realisations = FALSE, n_realisations = 15, derivatives = FALSE, newdata )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_smooth.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot mvgam smooth terms — plot_mvgam_smooth","text":"object list object returned mvgam trend_effects logical. TRUE trend_formula used model fitting, terms trend (.e. process) model plotted series integer specifying series set plotted smooth either character integer specifying smooth term plotted residuals logical. TRUE posterior quantiles partial residuals added plots 1-D smooths series ribbon rectangles. Partial residuals smooth term median Dunn-Smyth residuals obtained dropping term concerned model, leaving estimates fixed (.e. estimates term plus original median Dunn-Smyth residuals). Note mvgam works Dunn-Smyth residuals working residuals, used mgcv, magnitudes partial residuals different expect plot.gam. Interpretation similar though, partial residuals evenly scattered around smooth function function well estimated n_resid_bins integer specifying number bins group covariate plotting partial residuals. Setting argument high can make messy plots difficult interpret, setting low likely mask potentially useful patterns partial residuals. Default 25 realisations logical. TRUE, posterior realisations shown spaghetti plot, making easier visualise diversity possible functions. FALSE, default, empirical quantiles posterior distribution shown n_realisations integer specifying number posterior realisations plot, realisations = TRUE. Ignored otherwise derivatives logical. TRUE, additional plot returned show estimated 1st derivative specified smooth (Note, works univariate smooths) newdata Optional dataframe predicting smooth, containing least 'series' addition variables included linear predictor original model's formula. Note currently supported plotting univariate smooths","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_smooth.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot mvgam smooth terms — plot_mvgam_smooth","text":"base R graphics plot","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_smooth.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot mvgam smooth terms — plot_mvgam_smooth","text":"Smooth functions shown empirical quantiles (spaghetti plots) posterior partial expectations across sequence 500 values variable's min max, zeroing effects variables. present, univariate bivariate smooth plots allowed, though note bivariate smooths rely default behaviour plot.gam. nuanced visualisation, supply newdata just predicting gam model","code":""},{"path":[]},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_trend.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot mvgam latent trend for a specified series — plot_mvgam_trend","title":"Plot mvgam latent trend for a specified series — plot_mvgam_trend","text":"Plot mvgam latent trend specified series","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_trend.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot mvgam latent trend for a specified series — plot_mvgam_trend","text":"","code":"plot_mvgam_trend( object, series = 1, newdata, data_test, realisations = FALSE, n_realisations = 15, n_cores = 1, derivatives = FALSE, hide_xlabels = FALSE, xlab, ylab, ... )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_trend.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot mvgam latent trend for a specified series — plot_mvgam_trend","text":"object list object returned mvgam series integer specifying series set plotted newdata Optional dataframe list test data containing least 'series' 'time' addition variables included linear predictor original formula. data_test Deprecated. Still works place newdata users recommended use newdata instead seamless integration R workflows realisations logical. TRUE, posterior trend realisations shown spaghetti plot, making easier visualise diversity possible trend paths. FALSE, default, empirical quantiles posterior distribution shown n_realisations integer specifying number posterior realisations plot, realisations = TRUE. Ignored otherwise n_cores integer specifying number cores generating trend forecasts parallel derivatives logical. TRUE, additional plot returned show estimated 1st derivative estimated trend hide_xlabels logical. TRUE, xlabels printed allow user add custom labels using axis base R. Ignored derivatives = TRUE xlab label x axis. ylab label y axis. ... par graphical parameters.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_uncertainty.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot mvgam forecast uncertainty contributions for a specified series — plot_mvgam_uncertainty","title":"Plot mvgam forecast uncertainty contributions for a specified series — plot_mvgam_uncertainty","text":"Plot mvgam forecast uncertainty contributions specified series","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_uncertainty.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot mvgam forecast uncertainty contributions for a specified series — plot_mvgam_uncertainty","text":"","code":"plot_mvgam_uncertainty( object, series = 1, newdata, data_test, legend_position = \"topleft\", hide_xlabels = FALSE )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/plot_mvgam_uncertainty.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot mvgam forecast uncertainty contributions for a specified series — plot_mvgam_uncertainty","text":"object list object returned mvgam series integer specifying series set plotted newdata dataframe list containing least 'series' 'time' forecast horizon, addition variables included linear predictor formula data_test Deprecated. Still works place newdata users recommended use newdata instead seamless integration R workflows legend_position location may also specified setting x single keyword list: \"none\", \"bottomright\", \"bottom\", \"bottomleft\", \"left\", \"topleft\", \"top\", \"topright\", \"right\" \"center\". places legend inside plot frame given location (\"none\"). hide_xlabels logical. TRUE, xlabels printed allow user add custom labels using axis base R","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/portal_data.html","id":null,"dir":"Reference","previous_headings":"","what":"Portal Project rodent capture survey data — portal_data","title":"Portal Project rodent capture survey data — portal_data","text":"dataset containing timeseries select rodent species captures control plots Portal Project","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/portal_data.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Portal Project rodent capture survey data — portal_data","text":"","code":"portal_data"},{"path":"https://nicholasjclark.github.io/mvgam/reference/portal_data.html","id":"format","dir":"Reference","previous_headings":"","what":"Format","title":"Portal Project rodent capture survey data — portal_data","text":"dataframe containing following fields: moon time sampling lunar cycles DM Total captures species DM Total captures species DM Total captures species PP DM Total captures species OT year Sampling year month Sampling month mintemp Monthly mean minimum temperature precipitation Monthly mean precipitation ndvi Monthly mean Normalised Difference Vegetation Index","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/portal_data.html","id":"source","dir":"Reference","previous_headings":"","what":"Source","title":"Portal Project rodent capture survey data — portal_data","text":"https://www.weecology.org/data-projects/portal/","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/ppc.mvgam.html","id":null,"dir":"Reference","previous_headings":"","what":"Plot mvgam posterior predictive checks for a specified series — ppc.mvgam","title":"Plot mvgam posterior predictive checks for a specified series — ppc.mvgam","text":"Plot mvgam posterior predictive checks specified series","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/ppc.mvgam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Plot mvgam posterior predictive checks for a specified series — ppc.mvgam","text":"","code":"ppc(object, ...) # S3 method for mvgam ppc( object, newdata, data_test, series = 1, type = \"hist\", n_bins, legend_position, xlab, ylab, ... )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/ppc.mvgam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Plot mvgam posterior predictive checks for a specified series — ppc.mvgam","text":"object list object returned mvgam. See mvgam() ... par graphical parameters. newdata Optional dataframe list test data containing least 'series' 'time' forecast horizon, addition variables included linear predictor formula. included, observed values test data compared model's forecast distribution exploring biases model predictions. Note useful newdata also included fitting original model. data_test Deprecated. Still works place newdata users recommended use newdata instead seamless integration R workflows series integer specifying series set plotted type character specifying type posterior predictive check calculate plot. Valid options : 'rootogram', 'mean', 'hist', 'density', 'prop_zero', 'pit' 'cdf' n_bins integer specifying number bins use binning observed values plotting rootogram histogram. Default 50 bins rootogram, means >50 unique observed values, bins used prevent overplotting facilitate interpretation. Default histogram use number bins returned call hist base R legend_position location may also specified setting x single keyword list \"bottomright\", \"bottom\", \"bottomleft\", \"left\", \"topleft\", \"top\", \"topright\", \"right\" \"center\". places legend inside plot frame given location. alternatively, use \"none\" hide legend. xlab label x axis. ylab label y axis.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/ppc.mvgam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Plot mvgam posterior predictive checks for a specified series — ppc.mvgam","text":"base R graphics plot showing either posterior rootogram (type == 'rootogram'), predicted vs observed mean series (type == 'mean'), predicted vs observed proportion zeroes series (type == 'prop_zero'),predicted vs observed histogram series (type == 'hist'), kernel density empirical CDF estimates posterior predictions (type == 'density' type == 'cdf') Probability Integral Transform histogram (type == 'pit').","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/ppc.mvgam.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Plot mvgam posterior predictive checks for a specified series — ppc.mvgam","text":"Posterior predictions drawn fitted mvgam compared empirical distribution observed data specified series help evaluate model's ability generate unbiased predictions. plots apart 'rootogram', posterior predictions can also compared sample observations long observations included 'data_test' original model fit supplied . Rootograms currently plotted using 'hanging' style","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/predict.mvgam.html","id":null,"dir":"Reference","previous_headings":"","what":"Predict from the GAM component of an mvgam model — predict.mvgam","title":"Predict from the GAM component of an mvgam model — predict.mvgam","text":"Predict GAM component mvgam model","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/predict.mvgam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Predict from the GAM component of an mvgam model — predict.mvgam","text":"","code":"# S3 method for mvgam predict( object, newdata, data_test, type = \"link\", process_error = TRUE, n_cores = 1, ... )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/predict.mvgam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Predict from the GAM component of an mvgam model — predict.mvgam","text":"object list object returned mvgam newdata Optional dataframe list test data containing variables included linear predictor formula. supplied, predictions generated original observations used model fit. data_test Deprecated. Still works place newdata users recommended use newdata instead seamless integration R workflows type value link (default) linear predictor calculated link scale. expected used, predictions reflect expectation response (mean) ignore uncertainty observation process. response used, predictions take uncertainty observation process account return predictions outcome scale process_error Logical. TRUE dynamic trend model fit, expected uncertainty process model accounted using draws latent trend SD parameters. FALSE, uncertainty latent trend component ignored calculating predictions n_cores integer specifying number cores generating predictions parallel ... Ignored","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/predict.mvgam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Predict from the GAM component of an mvgam model — predict.mvgam","text":"matrix dimension n_samples x new_obs, n_samples number posterior samples fitted object n_obs number test observations newdata","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/predict.mvgam.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Predict from the GAM component of an mvgam model — predict.mvgam","text":"Note types predictions models include trend_formula, uncertainty dynamic trend component can ignored setting process_error = FALSE. However, trend_formula supplied model, predictions component ignored. process_error = TRUE, trend predictions ignore autocorrelation coefficients GP length scale coefficients, ultimately assuming process stationary. method similar types posterior predictions returned brms models using autocorrelated error predictions newdata. function therefore suited posterior simulation GAM components mvgam model, forecasting functions plot_mvgam_fc forecast.mvgam better suited generate h-step ahead forecasts respect temporal dynamics estimated latent trends.","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/print.mvgam.html","id":null,"dir":"Reference","previous_headings":"","what":"Summary for a fitted mvgam object — print.mvgam","title":"Summary for a fitted mvgam object — print.mvgam","text":"function takes fitted mvgam object prints quick summary","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/print.mvgam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Summary for a fitted mvgam object — print.mvgam","text":"","code":"# S3 method for mvgam print(x, ...)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/print.mvgam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Summary for a fitted mvgam object — print.mvgam","text":"x list object returned mvgam ... Ignored","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/print.mvgam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Summary for a fitted mvgam object — print.mvgam","text":"list printed -screen","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/print.mvgam.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Summary for a fitted mvgam object — print.mvgam","text":"brief summary model's call printed","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/print.mvgam.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Summary for a fitted mvgam object — print.mvgam","text":"Nicholas J Clark","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/score.mvgam_forecast.html","id":null,"dir":"Reference","previous_headings":"","what":"Compute probabilistic forecast scores for mvgam objects — score.mvgam_forecast","title":"Compute probabilistic forecast scores for mvgam objects — score.mvgam_forecast","text":"Compute probabilistic forecast scores mvgam objects","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/score.mvgam_forecast.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Compute probabilistic forecast scores for mvgam objects — score.mvgam_forecast","text":"","code":"# S3 method for mvgam_forecast score(object, score = \"crps\", log = FALSE, weights, interval_width = 0.9, ...) score(object, ...)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/score.mvgam_forecast.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Compute probabilistic forecast scores for mvgam objects — score.mvgam_forecast","text":"object mvgam_forecast object. See forecast.mvgam(). score character specifying type ranked probability score use evaluation. Options : variogram, drps crps log logical. forecasts truths logged prior scoring? often appropriate comparing performance models series vary observation ranges weights optional vector weights (length(weights) == n_series) weighting pairwise correlations evaluating variogram score multivariate forecasts. Useful -weighting series larger magnitude observations less interest forecasting. Ignored score != 'variogram' interval_width proportional value [0.05,0.95] defining forecast interval calculating coverage ... Ignored","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/score.mvgam_forecast.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Compute probabilistic forecast scores for mvgam objects — score.mvgam_forecast","text":"list containing scores 90% interval coverages per forecast horizon. score %% c('drps', 'crps'), list also contain return sum series-level scores per horizon. score == 'variogram', series-level scores computed score returned series. scores, in_interval column series-level slot binary indicator whether true value within forecast's corresponding posterior empirical quantiles","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/score.mvgam_forecast.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Compute probabilistic forecast scores for mvgam objects — score.mvgam_forecast","text":"","code":"if (FALSE) { #Simulate observations for three count-valued time series data <- sim_mvgam() #Fit a dynamic model using 'newdata' to automatically produce forecasts mod <- mvgam(y ~ 1, trend_model = 'RW', data = data$data_train, newdata = data$data_test) #Extract forecasts into a 'mvgam_forecast' object fc <- forecast(mod) #Score forecasts score(fc, score = 'drps') }"},{"path":"https://nicholasjclark.github.io/mvgam/reference/series_to_mvgam.html","id":null,"dir":"Reference","previous_headings":"","what":"This function converts univariate or multivariate time series (xts or ts objects)\r\nto the format necessary for mvgam — series_to_mvgam","title":"This function converts univariate or multivariate time series (xts or ts objects)\r\nto the format necessary for mvgam — series_to_mvgam","text":"function converts univariate multivariate time series (xts ts objects) format necessary mvgam","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/series_to_mvgam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"This function converts univariate or multivariate time series (xts or ts objects)\r\nto the format necessary for mvgam — series_to_mvgam","text":"","code":"series_to_mvgam(series, freq, train_prop = 0.85)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/series_to_mvgam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"This function converts univariate or multivariate time series (xts or ts objects)\r\nto the format necessary for mvgam — series_to_mvgam","text":"series xts ts object converted mvgam format freq integer. seasonal frequency series train_prop numeric stating proportion data use training. 0.25 0.95","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/series_to_mvgam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"This function converts univariate or multivariate time series (xts or ts objects)\r\nto the format necessary for mvgam — series_to_mvgam","text":"list object containing outputs needed mvgam, including 'data_train' 'data_test'","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/series_to_mvgam.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"This function converts univariate or multivariate time series (xts or ts objects)\r\nto the format necessary for mvgam — series_to_mvgam","text":"","code":"# A ts object example data(\"sunspots\") series <- cbind(sunspots, sunspots) colnames(series) <- c('blood', 'bone') head(series) #> blood bone #> [1,] 58.0 58.0 #> [2,] 62.6 62.6 #> [3,] 70.0 70.0 #> [4,] 55.7 55.7 #> [5,] 85.0 85.0 #> [6,] 83.5 83.5 series_to_mvgam(series, frequency(series), 0.85) #> $data_train #> y season year date series time #> 1 58.0 1 1749 1749-01-01 00:00:00 blood 1 #> 2 58.0 1 1749 1749-01-01 00:00:00 bone 1 #> 3 62.6 2 1749 1749-01-31 10:00:00 blood 2 #> 4 62.6 2 1749 1749-01-31 10:00:00 bone 2 #> 5 70.0 3 1749 1749-03-02 20:00:01 blood 3 #> 6 70.0 3 1749 1749-03-02 20:00:01 bone 3 #> 7 55.7 4 1749 1749-04-02 06:00:00 blood 4 #> 8 55.7 4 1749 1749-04-02 06:00:00 bone 4 #> 9 85.0 5 1749 1749-05-02 16:00:00 blood 5 #> 10 85.0 5 1749 1749-05-02 16:00:00 bone 5 #> 11 83.5 6 1749 1749-06-02 02:00:01 blood 6 #> 12 83.5 6 1749 1749-06-02 02:00:01 bone 6 #> 13 94.8 7 1749 1749-07-02 12:00:00 blood 7 #> 14 94.8 7 1749 1749-07-02 12:00:00 bone 7 #> 15 66.3 8 1749 1749-08-01 22:00:00 blood 8 #> 16 66.3 8 1749 1749-08-01 22:00:00 bone 8 #> 17 75.9 9 1749 1749-09-01 08:00:01 blood 9 #> 18 75.9 9 1749 1749-09-01 08:00:01 bone 9 #> 19 75.5 10 1749 1749-10-01 18:00:00 blood 10 #> 20 75.5 10 1749 1749-10-01 18:00:00 bone 10 #> 21 158.6 11 1749 1749-11-01 04:00:00 blood 11 #> 22 158.6 11 1749 1749-11-01 04:00:00 bone 11 #> 23 85.2 12 1749 1749-12-01 14:00:01 blood 12 #> 24 85.2 12 1749 1749-12-01 14:00:01 bone 12 #> 25 73.3 1 1750 1750-01-01 00:00:00 blood 13 #> 26 73.3 1 1750 1750-01-01 00:00:00 bone 13 #> 27 75.9 2 1750 1750-01-31 10:00:00 blood 14 #> 28 75.9 2 1750 1750-01-31 10:00:00 bone 14 #> 29 89.2 3 1750 1750-03-02 20:00:01 blood 15 #> 30 89.2 3 1750 1750-03-02 20:00:01 bone 15 #> 31 88.3 4 1750 1750-04-02 06:00:00 blood 16 #> 32 88.3 4 1750 1750-04-02 06:00:00 bone 16 #> 33 90.0 5 1750 1750-05-02 16:00:00 blood 17 #> 34 90.0 5 1750 1750-05-02 16:00:00 bone 17 #> 35 100.0 6 1750 1750-06-02 02:00:01 blood 18 #> 36 100.0 6 1750 1750-06-02 02:00:01 bone 18 #> 37 85.4 7 1750 1750-07-02 12:00:00 blood 19 #> 38 85.4 7 1750 1750-07-02 12:00:00 bone 19 #> 39 103.0 8 1750 1750-08-01 22:00:00 blood 20 #> 40 103.0 8 1750 1750-08-01 22:00:00 bone 20 #> 41 91.2 9 1750 1750-09-01 08:00:01 blood 21 #> 42 91.2 9 1750 1750-09-01 08:00:01 bone 21 #> 43 65.7 10 1750 1750-10-01 18:00:00 blood 22 #> 44 65.7 10 1750 1750-10-01 18:00:00 bone 22 #> 45 63.3 11 1750 1750-11-01 04:00:00 blood 23 #> 46 63.3 11 1750 1750-11-01 04:00:00 bone 23 #> 47 75.4 12 1750 1750-12-01 14:00:01 blood 24 #> 48 75.4 12 1750 1750-12-01 14:00:01 bone 24 #> 49 70.0 1 1751 1751-01-01 00:00:00 blood 25 #> 50 70.0 1 1751 1751-01-01 00:00:00 bone 25 #> 51 43.5 2 1751 1751-01-31 10:00:00 blood 26 #> 52 43.5 2 1751 1751-01-31 10:00:00 bone 26 #> 53 45.3 3 1751 1751-03-02 20:00:01 blood 27 #> 54 45.3 3 1751 1751-03-02 20:00:01 bone 27 #> 55 56.4 4 1751 1751-04-02 06:00:00 blood 28 #> 56 56.4 4 1751 1751-04-02 06:00:00 bone 28 #> 57 60.7 5 1751 1751-05-02 16:00:00 blood 29 #> 58 60.7 5 1751 1751-05-02 16:00:00 bone 29 #> 59 50.7 6 1751 1751-06-02 02:00:01 blood 30 #> 60 50.7 6 1751 1751-06-02 02:00:01 bone 30 #> 61 66.3 7 1751 1751-07-02 12:00:00 blood 31 #> 62 66.3 7 1751 1751-07-02 12:00:00 bone 31 #> 63 59.8 8 1751 1751-08-01 22:00:00 blood 32 #> 64 59.8 8 1751 1751-08-01 22:00:00 bone 32 #> 65 23.5 9 1751 1751-09-01 08:00:01 blood 33 #> 66 23.5 9 1751 1751-09-01 08:00:01 bone 33 #> 67 23.2 10 1751 1751-10-01 18:00:00 blood 34 #> 68 23.2 10 1751 1751-10-01 18:00:00 bone 34 #> 69 28.5 11 1751 1751-11-01 04:00:00 blood 35 #> 70 28.5 11 1751 1751-11-01 04:00:00 bone 35 #> 71 44.0 12 1751 1751-12-01 14:00:01 blood 36 #> 72 44.0 12 1751 1751-12-01 14:00:01 bone 36 #> 73 35.0 1 1752 1752-01-01 00:00:00 blood 37 #> 74 35.0 1 1752 1752-01-01 00:00:00 bone 37 #> 75 50.0 2 1752 1752-01-31 12:00:00 blood 38 #> 76 50.0 2 1752 1752-01-31 12:00:00 bone 38 #> 77 71.0 3 1752 1752-03-02 00:00:01 blood 39 #> 78 71.0 3 1752 1752-03-02 00:00:01 bone 39 #> 79 59.3 4 1752 1752-04-01 12:00:00 blood 40 #> 80 59.3 4 1752 1752-04-01 12:00:00 bone 40 #> 81 59.7 5 1752 1752-05-02 00:00:00 blood 41 #> 82 59.7 5 1752 1752-05-02 00:00:00 bone 41 #> 83 39.6 6 1752 1752-06-01 12:00:01 blood 42 #> 84 39.6 6 1752 1752-06-01 12:00:01 bone 42 #> 85 78.4 7 1752 1752-07-02 00:00:00 blood 43 #> 86 78.4 7 1752 1752-07-02 00:00:00 bone 43 #> 87 29.3 8 1752 1752-08-01 12:00:00 blood 44 #> 88 29.3 8 1752 1752-08-01 12:00:00 bone 44 #> 89 27.1 9 1752 1752-09-01 00:00:01 blood 45 #> 90 27.1 9 1752 1752-09-01 00:00:01 bone 45 #> 91 46.6 10 1752 1752-10-01 12:00:00 blood 46 #> 92 46.6 10 1752 1752-10-01 12:00:00 bone 46 #> 93 37.6 11 1752 1752-11-01 00:00:00 blood 47 #> 94 37.6 11 1752 1752-11-01 00:00:00 bone 47 #> 95 40.0 12 1752 1752-12-01 12:00:01 blood 48 #> 96 40.0 12 1752 1752-12-01 12:00:01 bone 48 #> 97 44.0 1 1753 1753-01-01 00:00:00 blood 49 #> 98 44.0 1 1753 1753-01-01 00:00:00 bone 49 #> 99 32.0 2 1753 1753-01-31 10:00:00 blood 50 #> 100 32.0 2 1753 1753-01-31 10:00:00 bone 50 #> 101 45.7 3 1753 1753-03-02 20:00:01 blood 51 #> 102 45.7 3 1753 1753-03-02 20:00:01 bone 51 #> 103 38.0 4 1753 1753-04-02 06:00:00 blood 52 #> 104 38.0 4 1753 1753-04-02 06:00:00 bone 52 #> 105 36.0 5 1753 1753-05-02 16:00:00 blood 53 #> 106 36.0 5 1753 1753-05-02 16:00:00 bone 53 #> 107 31.7 6 1753 1753-06-02 02:00:01 blood 54 #> 108 31.7 6 1753 1753-06-02 02:00:01 bone 54 #> 109 22.2 7 1753 1753-07-02 12:00:00 blood 55 #> 110 22.2 7 1753 1753-07-02 12:00:00 bone 55 #> 111 39.0 8 1753 1753-08-01 22:00:00 blood 56 #> 112 39.0 8 1753 1753-08-01 22:00:00 bone 56 #> 113 28.0 9 1753 1753-09-01 08:00:01 blood 57 #> 114 28.0 9 1753 1753-09-01 08:00:01 bone 57 #> 115 25.0 10 1753 1753-10-01 18:00:00 blood 58 #> 116 25.0 10 1753 1753-10-01 18:00:00 bone 58 #> 117 20.0 11 1753 1753-11-01 04:00:00 blood 59 #> 118 20.0 11 1753 1753-11-01 04:00:00 bone 59 #> 119 6.7 12 1753 1753-12-01 14:00:01 blood 60 #> 120 6.7 12 1753 1753-12-01 14:00:01 bone 60 #> 121 0.0 1 1754 1754-01-01 00:00:00 blood 61 #> 122 0.0 1 1754 1754-01-01 00:00:00 bone 61 #> 123 3.0 2 1754 1754-01-31 10:00:00 blood 62 #> 124 3.0 2 1754 1754-01-31 10:00:00 bone 62 #> 125 1.7 3 1754 1754-03-02 20:00:01 blood 63 #> 126 1.7 3 1754 1754-03-02 20:00:01 bone 63 #> 127 13.7 4 1754 1754-04-02 06:00:00 blood 64 #> 128 13.7 4 1754 1754-04-02 06:00:00 bone 64 #> 129 20.7 5 1754 1754-05-02 16:00:00 blood 65 #> 130 20.7 5 1754 1754-05-02 16:00:00 bone 65 #> 131 26.7 6 1754 1754-06-02 02:00:01 blood 66 #> 132 26.7 6 1754 1754-06-02 02:00:01 bone 66 #> 133 18.8 7 1754 1754-07-02 12:00:00 blood 67 #> 134 18.8 7 1754 1754-07-02 12:00:00 bone 67 #> 135 12.3 8 1754 1754-08-01 22:00:00 blood 68 #> 136 12.3 8 1754 1754-08-01 22:00:00 bone 68 #> 137 8.2 9 1754 1754-09-01 08:00:01 blood 69 #> 138 8.2 9 1754 1754-09-01 08:00:01 bone 69 #> 139 24.1 10 1754 1754-10-01 18:00:00 blood 70 #> 140 24.1 10 1754 1754-10-01 18:00:00 bone 70 #> 141 13.2 11 1754 1754-11-01 04:00:00 blood 71 #> 142 13.2 11 1754 1754-11-01 04:00:00 bone 71 #> 143 4.2 12 1754 1754-12-01 14:00:01 blood 72 #> 144 4.2 12 1754 1754-12-01 14:00:01 bone 72 #> 145 10.2 1 1755 1755-01-01 00:00:00 blood 73 #> 146 10.2 1 1755 1755-01-01 00:00:00 bone 73 #> 147 11.2 2 1755 1755-01-31 10:00:00 blood 74 #> 148 11.2 2 1755 1755-01-31 10:00:00 bone 74 #> 149 6.8 3 1755 1755-03-02 20:00:01 blood 75 #> 150 6.8 3 1755 1755-03-02 20:00:01 bone 75 #> 151 6.5 4 1755 1755-04-02 06:00:00 blood 76 #> 152 6.5 4 1755 1755-04-02 06:00:00 bone 76 #> 153 0.0 5 1755 1755-05-02 16:00:00 blood 77 #> 154 0.0 5 1755 1755-05-02 16:00:00 bone 77 #> 155 0.0 6 1755 1755-06-02 02:00:01 blood 78 #> 156 0.0 6 1755 1755-06-02 02:00:01 bone 78 #> 157 8.6 7 1755 1755-07-02 12:00:00 blood 79 #> 158 8.6 7 1755 1755-07-02 12:00:00 bone 79 #> 159 3.2 8 1755 1755-08-01 22:00:00 blood 80 #> 160 3.2 8 1755 1755-08-01 22:00:00 bone 80 #> 161 17.8 9 1755 1755-09-01 08:00:01 blood 81 #> 162 17.8 9 1755 1755-09-01 08:00:01 bone 81 #> 163 23.7 10 1755 1755-10-01 18:00:00 blood 82 #> 164 23.7 10 1755 1755-10-01 18:00:00 bone 82 #> 165 6.8 11 1755 1755-11-01 04:00:00 blood 83 #> 166 6.8 11 1755 1755-11-01 04:00:00 bone 83 #> 167 20.0 12 1755 1755-12-01 14:00:01 blood 84 #> 168 20.0 12 1755 1755-12-01 14:00:01 bone 84 #> 169 12.5 1 1756 1756-01-01 00:00:00 blood 85 #> 170 12.5 1 1756 1756-01-01 00:00:00 bone 85 #> 171 7.1 2 1756 1756-01-31 12:00:00 blood 86 #> 172 7.1 2 1756 1756-01-31 12:00:00 bone 86 #> 173 5.4 3 1756 1756-03-02 00:00:01 blood 87 #> 174 5.4 3 1756 1756-03-02 00:00:01 bone 87 #> 175 9.4 4 1756 1756-04-01 12:00:00 blood 88 #> 176 9.4 4 1756 1756-04-01 12:00:00 bone 88 #> 177 12.5 5 1756 1756-05-02 00:00:00 blood 89 #> 178 12.5 5 1756 1756-05-02 00:00:00 bone 89 #> 179 12.9 6 1756 1756-06-01 12:00:01 blood 90 #> 180 12.9 6 1756 1756-06-01 12:00:01 bone 90 #> 181 3.6 7 1756 1756-07-02 00:00:00 blood 91 #> 182 3.6 7 1756 1756-07-02 00:00:00 bone 91 #> 183 6.4 8 1756 1756-08-01 12:00:00 blood 92 #> 184 6.4 8 1756 1756-08-01 12:00:00 bone 92 #> 185 11.8 9 1756 1756-09-01 00:00:01 blood 93 #> 186 11.8 9 1756 1756-09-01 00:00:01 bone 93 #> 187 14.3 10 1756 1756-10-01 12:00:00 blood 94 #> 188 14.3 10 1756 1756-10-01 12:00:00 bone 94 #> 189 17.0 11 1756 1756-11-01 00:00:00 blood 95 #> 190 17.0 11 1756 1756-11-01 00:00:00 bone 95 #> 191 9.4 12 1756 1756-12-01 12:00:01 blood 96 #> 192 9.4 12 1756 1756-12-01 12:00:01 bone 96 #> 193 14.1 1 1757 1757-01-01 00:00:00 blood 97 #> 194 14.1 1 1757 1757-01-01 00:00:00 bone 97 #> 195 21.2 2 1757 1757-01-31 10:00:00 blood 98 #> 196 21.2 2 1757 1757-01-31 10:00:00 bone 98 #> 197 26.2 3 1757 1757-03-02 20:00:01 blood 99 #> 198 26.2 3 1757 1757-03-02 20:00:01 bone 99 #> 199 30.0 4 1757 1757-04-02 06:00:00 blood 100 #> 200 30.0 4 1757 1757-04-02 06:00:00 bone 100 #> 201 38.1 5 1757 1757-05-02 16:00:00 blood 101 #> 202 38.1 5 1757 1757-05-02 16:00:00 bone 101 #> 203 12.8 6 1757 1757-06-02 02:00:01 blood 102 #> 204 12.8 6 1757 1757-06-02 02:00:01 bone 102 #> 205 25.0 7 1757 1757-07-02 12:00:00 blood 103 #> 206 25.0 7 1757 1757-07-02 12:00:00 bone 103 #> 207 51.3 8 1757 1757-08-01 22:00:00 blood 104 #> 208 51.3 8 1757 1757-08-01 22:00:00 bone 104 #> 209 39.7 9 1757 1757-09-01 08:00:01 blood 105 #> 210 39.7 9 1757 1757-09-01 08:00:01 bone 105 #> 211 32.5 10 1757 1757-10-01 18:00:00 blood 106 #> 212 32.5 10 1757 1757-10-01 18:00:00 bone 106 #> 213 64.7 11 1757 1757-11-01 04:00:00 blood 107 #> 214 64.7 11 1757 1757-11-01 04:00:00 bone 107 #> 215 33.5 12 1757 1757-12-01 14:00:01 blood 108 #> 216 33.5 12 1757 1757-12-01 14:00:01 bone 108 #> 217 37.6 1 1758 1758-01-01 00:00:00 blood 109 #> 218 37.6 1 1758 1758-01-01 00:00:00 bone 109 #> 219 52.0 2 1758 1758-01-31 10:00:00 blood 110 #> 220 52.0 2 1758 1758-01-31 10:00:00 bone 110 #> 221 49.0 3 1758 1758-03-02 20:00:01 blood 111 #> 222 49.0 3 1758 1758-03-02 20:00:01 bone 111 #> 223 72.3 4 1758 1758-04-02 06:00:00 blood 112 #> 224 72.3 4 1758 1758-04-02 06:00:00 bone 112 #> 225 46.4 5 1758 1758-05-02 16:00:00 blood 113 #> 226 46.4 5 1758 1758-05-02 16:00:00 bone 113 #> 227 45.0 6 1758 1758-06-02 02:00:01 blood 114 #> 228 45.0 6 1758 1758-06-02 02:00:01 bone 114 #> 229 44.0 7 1758 1758-07-02 12:00:00 blood 115 #> 230 44.0 7 1758 1758-07-02 12:00:00 bone 115 #> 231 38.7 8 1758 1758-08-01 22:00:00 blood 116 #> 232 38.7 8 1758 1758-08-01 22:00:00 bone 116 #> 233 62.5 9 1758 1758-09-01 08:00:01 blood 117 #> 234 62.5 9 1758 1758-09-01 08:00:01 bone 117 #> 235 37.7 10 1758 1758-10-01 18:00:00 blood 118 #> 236 37.7 10 1758 1758-10-01 18:00:00 bone 118 #> 237 43.0 11 1758 1758-11-01 04:00:00 blood 119 #> 238 43.0 11 1758 1758-11-01 04:00:00 bone 119 #> 239 43.0 12 1758 1758-12-01 14:00:01 blood 120 #> 240 43.0 12 1758 1758-12-01 14:00:01 bone 120 #> 241 48.3 1 1759 1759-01-01 00:00:00 blood 121 #> 242 48.3 1 1759 1759-01-01 00:00:00 bone 121 #> 243 44.0 2 1759 1759-01-31 10:00:00 blood 122 #> 244 44.0 2 1759 1759-01-31 10:00:00 bone 122 #> 245 46.8 3 1759 1759-03-02 20:00:01 blood 123 #> 246 46.8 3 1759 1759-03-02 20:00:01 bone 123 #> 247 47.0 4 1759 1759-04-02 06:00:00 blood 124 #> 248 47.0 4 1759 1759-04-02 06:00:00 bone 124 #> 249 49.0 5 1759 1759-05-02 16:00:00 blood 125 #> 250 49.0 5 1759 1759-05-02 16:00:00 bone 125 #> 251 50.0 6 1759 1759-06-02 02:00:01 blood 126 #> 252 50.0 6 1759 1759-06-02 02:00:01 bone 126 #> 253 51.0 7 1759 1759-07-02 12:00:00 blood 127 #> 254 51.0 7 1759 1759-07-02 12:00:00 bone 127 #> 255 71.3 8 1759 1759-08-01 22:00:00 blood 128 #> 256 71.3 8 1759 1759-08-01 22:00:00 bone 128 #> 257 77.2 9 1759 1759-09-01 08:00:01 blood 129 #> 258 77.2 9 1759 1759-09-01 08:00:01 bone 129 #> 259 59.7 10 1759 1759-10-01 18:00:00 blood 130 #> 260 59.7 10 1759 1759-10-01 18:00:00 bone 130 #> 261 46.3 11 1759 1759-11-01 04:00:00 blood 131 #> 262 46.3 11 1759 1759-11-01 04:00:00 bone 131 #> 263 57.0 12 1759 1759-12-01 14:00:01 blood 132 #> 264 57.0 12 1759 1759-12-01 14:00:01 bone 132 #> 265 67.3 1 1760 1760-01-01 00:00:00 blood 133 #> 266 67.3 1 1760 1760-01-01 00:00:00 bone 133 #> 267 59.5 2 1760 1760-01-31 12:00:00 blood 134 #> 268 59.5 2 1760 1760-01-31 12:00:00 bone 134 #> 269 74.7 3 1760 1760-03-02 00:00:01 blood 135 #> 270 74.7 3 1760 1760-03-02 00:00:01 bone 135 #> 271 58.3 4 1760 1760-04-01 12:00:00 blood 136 #> 272 58.3 4 1760 1760-04-01 12:00:00 bone 136 #> 273 72.0 5 1760 1760-05-02 00:00:00 blood 137 #> 274 72.0 5 1760 1760-05-02 00:00:00 bone 137 #> 275 48.3 6 1760 1760-06-01 12:00:01 blood 138 #> 276 48.3 6 1760 1760-06-01 12:00:01 bone 138 #> 277 66.0 7 1760 1760-07-02 00:00:00 blood 139 #> 278 66.0 7 1760 1760-07-02 00:00:00 bone 139 #> 279 75.6 8 1760 1760-08-01 12:00:00 blood 140 #> 280 75.6 8 1760 1760-08-01 12:00:00 bone 140 #> 281 61.3 9 1760 1760-09-01 00:00:01 blood 141 #> 282 61.3 9 1760 1760-09-01 00:00:01 bone 141 #> 283 50.6 10 1760 1760-10-01 12:00:00 blood 142 #> 284 50.6 10 1760 1760-10-01 12:00:00 bone 142 #> 285 59.7 11 1760 1760-11-01 00:00:00 blood 143 #> 286 59.7 11 1760 1760-11-01 00:00:00 bone 143 #> 287 61.0 12 1760 1760-12-01 12:00:01 blood 144 #> 288 61.0 12 1760 1760-12-01 12:00:01 bone 144 #> 289 70.0 1 1761 1761-01-01 00:00:00 blood 145 #> 290 70.0 1 1761 1761-01-01 00:00:00 bone 145 #> 291 91.0 2 1761 1761-01-31 10:00:00 blood 146 #> 292 91.0 2 1761 1761-01-31 10:00:00 bone 146 #> 293 80.7 3 1761 1761-03-02 20:00:01 blood 147 #> 294 80.7 3 1761 1761-03-02 20:00:01 bone 147 #> 295 71.7 4 1761 1761-04-02 06:00:00 blood 148 #> 296 71.7 4 1761 1761-04-02 06:00:00 bone 148 #> 297 107.2 5 1761 1761-05-02 16:00:00 blood 149 #> 298 107.2 5 1761 1761-05-02 16:00:00 bone 149 #> 299 99.3 6 1761 1761-06-02 02:00:01 blood 150 #> 300 99.3 6 1761 1761-06-02 02:00:01 bone 150 #> 301 94.1 7 1761 1761-07-02 12:00:00 blood 151 #> 302 94.1 7 1761 1761-07-02 12:00:00 bone 151 #> 303 91.1 8 1761 1761-08-01 22:00:00 blood 152 #> 304 91.1 8 1761 1761-08-01 22:00:00 bone 152 #> 305 100.7 9 1761 1761-09-01 08:00:01 blood 153 #> 306 100.7 9 1761 1761-09-01 08:00:01 bone 153 #> 307 88.7 10 1761 1761-10-01 18:00:00 blood 154 #> 308 88.7 10 1761 1761-10-01 18:00:00 bone 154 #> 309 89.7 11 1761 1761-11-01 04:00:00 blood 155 #> 310 89.7 11 1761 1761-11-01 04:00:00 bone 155 #> 311 46.0 12 1761 1761-12-01 14:00:01 blood 156 #> 312 46.0 12 1761 1761-12-01 14:00:01 bone 156 #> 313 43.8 1 1762 1762-01-01 00:00:00 blood 157 #> 314 43.8 1 1762 1762-01-01 00:00:00 bone 157 #> 315 72.8 2 1762 1762-01-31 10:00:00 blood 158 #> 316 72.8 2 1762 1762-01-31 10:00:00 bone 158 #> 317 45.7 3 1762 1762-03-02 20:00:01 blood 159 #> 318 45.7 3 1762 1762-03-02 20:00:01 bone 159 #> 319 60.2 4 1762 1762-04-02 06:00:00 blood 160 #> 320 60.2 4 1762 1762-04-02 06:00:00 bone 160 #> 321 39.9 5 1762 1762-05-02 16:00:00 blood 161 #> 322 39.9 5 1762 1762-05-02 16:00:00 bone 161 #> 323 77.1 6 1762 1762-06-02 02:00:01 blood 162 #> 324 77.1 6 1762 1762-06-02 02:00:01 bone 162 #> 325 33.8 7 1762 1762-07-02 12:00:00 blood 163 #> 326 33.8 7 1762 1762-07-02 12:00:00 bone 163 #> 327 67.7 8 1762 1762-08-01 22:00:00 blood 164 #> 328 67.7 8 1762 1762-08-01 22:00:00 bone 164 #> 329 68.5 9 1762 1762-09-01 08:00:01 blood 165 #> 330 68.5 9 1762 1762-09-01 08:00:01 bone 165 #> 331 69.3 10 1762 1762-10-01 18:00:00 blood 166 #> 332 69.3 10 1762 1762-10-01 18:00:00 bone 166 #> 333 77.8 11 1762 1762-11-01 04:00:00 blood 167 #> 334 77.8 11 1762 1762-11-01 04:00:00 bone 167 #> 335 77.2 12 1762 1762-12-01 14:00:01 blood 168 #> 336 77.2 12 1762 1762-12-01 14:00:01 bone 168 #> 337 56.5 1 1763 1763-01-01 00:00:00 blood 169 #> 338 56.5 1 1763 1763-01-01 00:00:00 bone 169 #> 339 31.9 2 1763 1763-01-31 10:00:00 blood 170 #> 340 31.9 2 1763 1763-01-31 10:00:00 bone 170 #> 341 34.2 3 1763 1763-03-02 20:00:01 blood 171 #> 342 34.2 3 1763 1763-03-02 20:00:01 bone 171 #> 343 32.9 4 1763 1763-04-02 06:00:00 blood 172 #> 344 32.9 4 1763 1763-04-02 06:00:00 bone 172 #> 345 32.7 5 1763 1763-05-02 16:00:00 blood 173 #> 346 32.7 5 1763 1763-05-02 16:00:00 bone 173 #> 347 35.8 6 1763 1763-06-02 02:00:01 blood 174 #> 348 35.8 6 1763 1763-06-02 02:00:01 bone 174 #> 349 54.2 7 1763 1763-07-02 12:00:00 blood 175 #> 350 54.2 7 1763 1763-07-02 12:00:00 bone 175 #> 351 26.5 8 1763 1763-08-01 22:00:00 blood 176 #> 352 26.5 8 1763 1763-08-01 22:00:00 bone 176 #> 353 68.1 9 1763 1763-09-01 08:00:01 blood 177 #> 354 68.1 9 1763 1763-09-01 08:00:01 bone 177 #> 355 46.3 10 1763 1763-10-01 18:00:00 blood 178 #> 356 46.3 10 1763 1763-10-01 18:00:00 bone 178 #> 357 60.9 11 1763 1763-11-01 04:00:00 blood 179 #> 358 60.9 11 1763 1763-11-01 04:00:00 bone 179 #> 359 61.4 12 1763 1763-12-01 14:00:01 blood 180 #> 360 61.4 12 1763 1763-12-01 14:00:01 bone 180 #> 361 59.7 1 1764 1764-01-01 00:00:00 blood 181 #> 362 59.7 1 1764 1764-01-01 00:00:00 bone 181 #> 363 59.7 2 1764 1764-01-31 12:00:00 blood 182 #> 364 59.7 2 1764 1764-01-31 12:00:00 bone 182 #> 365 40.2 3 1764 1764-03-02 00:00:01 blood 183 #> 366 40.2 3 1764 1764-03-02 00:00:01 bone 183 #> 367 34.4 4 1764 1764-04-01 12:00:00 blood 184 #> 368 34.4 4 1764 1764-04-01 12:00:00 bone 184 #> 369 44.3 5 1764 1764-05-02 00:00:00 blood 185 #> 370 44.3 5 1764 1764-05-02 00:00:00 bone 185 #> 371 30.0 6 1764 1764-06-01 12:00:01 blood 186 #> 372 30.0 6 1764 1764-06-01 12:00:01 bone 186 #> 373 30.0 7 1764 1764-07-02 00:00:00 blood 187 #> 374 30.0 7 1764 1764-07-02 00:00:00 bone 187 #> 375 30.0 8 1764 1764-08-01 12:00:00 blood 188 #> 376 30.0 8 1764 1764-08-01 12:00:00 bone 188 #> 377 28.2 9 1764 1764-09-01 00:00:01 blood 189 #> 378 28.2 9 1764 1764-09-01 00:00:01 bone 189 #> 379 28.0 10 1764 1764-10-01 12:00:00 blood 190 #> 380 28.0 10 1764 1764-10-01 12:00:00 bone 190 #> 381 26.0 11 1764 1764-11-01 00:00:00 blood 191 #> 382 26.0 11 1764 1764-11-01 00:00:00 bone 191 #> 383 25.7 12 1764 1764-12-01 12:00:01 blood 192 #> 384 25.7 12 1764 1764-12-01 12:00:01 bone 192 #> 385 24.0 1 1765 1765-01-01 00:00:00 blood 193 #> 386 24.0 1 1765 1765-01-01 00:00:00 bone 193 #> 387 26.0 2 1765 1765-01-31 10:00:00 blood 194 #> 388 26.0 2 1765 1765-01-31 10:00:00 bone 194 #> 389 25.0 3 1765 1765-03-02 20:00:01 blood 195 #> 390 25.0 3 1765 1765-03-02 20:00:01 bone 195 #> 391 22.0 4 1765 1765-04-02 06:00:00 blood 196 #> 392 22.0 4 1765 1765-04-02 06:00:00 bone 196 #> 393 20.2 5 1765 1765-05-02 16:00:00 blood 197 #> 394 20.2 5 1765 1765-05-02 16:00:00 bone 197 #> 395 20.0 6 1765 1765-06-02 02:00:01 blood 198 #> 396 20.0 6 1765 1765-06-02 02:00:01 bone 198 #> 397 27.0 7 1765 1765-07-02 12:00:00 blood 199 #> 398 27.0 7 1765 1765-07-02 12:00:00 bone 199 #> 399 29.7 8 1765 1765-08-01 22:00:00 blood 200 #> 400 29.7 8 1765 1765-08-01 22:00:00 bone 200 #> 401 16.0 9 1765 1765-09-01 08:00:01 blood 201 #> 402 16.0 9 1765 1765-09-01 08:00:01 bone 201 #> 403 14.0 10 1765 1765-10-01 18:00:00 blood 202 #> 404 14.0 10 1765 1765-10-01 18:00:00 bone 202 #> 405 14.0 11 1765 1765-11-01 04:00:00 blood 203 #> 406 14.0 11 1765 1765-11-01 04:00:00 bone 203 #> 407 13.0 12 1765 1765-12-01 14:00:01 blood 204 #> 408 13.0 12 1765 1765-12-01 14:00:01 bone 204 #> 409 12.0 1 1766 1766-01-01 00:00:00 blood 205 #> 410 12.0 1 1766 1766-01-01 00:00:00 bone 205 #> 411 11.0 2 1766 1766-01-31 10:00:00 blood 206 #> 412 11.0 2 1766 1766-01-31 10:00:00 bone 206 #> 413 36.6 3 1766 1766-03-02 20:00:01 blood 207 #> 414 36.6 3 1766 1766-03-02 20:00:01 bone 207 #> 415 6.0 4 1766 1766-04-02 06:00:00 blood 208 #> 416 6.0 4 1766 1766-04-02 06:00:00 bone 208 #> 417 26.8 5 1766 1766-05-02 16:00:00 blood 209 #> 418 26.8 5 1766 1766-05-02 16:00:00 bone 209 #> 419 3.0 6 1766 1766-06-02 02:00:01 blood 210 #> 420 3.0 6 1766 1766-06-02 02:00:01 bone 210 #> 421 3.3 7 1766 1766-07-02 12:00:00 blood 211 #> 422 3.3 7 1766 1766-07-02 12:00:00 bone 211 #> 423 4.0 8 1766 1766-08-01 22:00:00 blood 212 #> 424 4.0 8 1766 1766-08-01 22:00:00 bone 212 #> 425 4.3 9 1766 1766-09-01 08:00:01 blood 213 #> 426 4.3 9 1766 1766-09-01 08:00:01 bone 213 #> 427 5.0 10 1766 1766-10-01 18:00:00 blood 214 #> 428 5.0 10 1766 1766-10-01 18:00:00 bone 214 #> 429 5.7 11 1766 1766-11-01 04:00:00 blood 215 #> 430 5.7 11 1766 1766-11-01 04:00:00 bone 215 #> 431 19.2 12 1766 1766-12-01 14:00:01 blood 216 #> 432 19.2 12 1766 1766-12-01 14:00:01 bone 216 #> 433 27.4 1 1767 1767-01-01 00:00:00 blood 217 #> 434 27.4 1 1767 1767-01-01 00:00:00 bone 217 #> 435 30.0 2 1767 1767-01-31 10:00:00 blood 218 #> 436 30.0 2 1767 1767-01-31 10:00:00 bone 218 #> 437 43.0 3 1767 1767-03-02 20:00:01 blood 219 #> 438 43.0 3 1767 1767-03-02 20:00:01 bone 219 #> 439 32.9 4 1767 1767-04-02 06:00:00 blood 220 #> 440 32.9 4 1767 1767-04-02 06:00:00 bone 220 #> 441 29.8 5 1767 1767-05-02 16:00:00 blood 221 #> 442 29.8 5 1767 1767-05-02 16:00:00 bone 221 #> 443 33.3 6 1767 1767-06-02 02:00:01 blood 222 #> 444 33.3 6 1767 1767-06-02 02:00:01 bone 222 #> 445 21.9 7 1767 1767-07-02 12:00:00 blood 223 #> 446 21.9 7 1767 1767-07-02 12:00:00 bone 223 #> 447 40.8 8 1767 1767-08-01 22:00:00 blood 224 #> 448 40.8 8 1767 1767-08-01 22:00:00 bone 224 #> 449 42.7 9 1767 1767-09-01 08:00:01 blood 225 #> 450 42.7 9 1767 1767-09-01 08:00:01 bone 225 #> 451 44.1 10 1767 1767-10-01 18:00:00 blood 226 #> 452 44.1 10 1767 1767-10-01 18:00:00 bone 226 #> 453 54.7 11 1767 1767-11-01 04:00:00 blood 227 #> 454 54.7 11 1767 1767-11-01 04:00:00 bone 227 #> 455 53.3 12 1767 1767-12-01 14:00:01 blood 228 #> 456 53.3 12 1767 1767-12-01 14:00:01 bone 228 #> 457 53.5 1 1768 1768-01-01 00:00:00 blood 229 #> 458 53.5 1 1768 1768-01-01 00:00:00 bone 229 #> 459 66.1 2 1768 1768-01-31 12:00:00 blood 230 #> 460 66.1 2 1768 1768-01-31 12:00:00 bone 230 #> 461 46.3 3 1768 1768-03-02 00:00:01 blood 231 #> 462 46.3 3 1768 1768-03-02 00:00:01 bone 231 #> 463 42.7 4 1768 1768-04-01 12:00:00 blood 232 #> 464 42.7 4 1768 1768-04-01 12:00:00 bone 232 #> 465 77.7 5 1768 1768-05-02 00:00:00 blood 233 #> 466 77.7 5 1768 1768-05-02 00:00:00 bone 233 #> 467 77.4 6 1768 1768-06-01 12:00:01 blood 234 #> 468 77.4 6 1768 1768-06-01 12:00:01 bone 234 #> 469 52.6 7 1768 1768-07-02 00:00:00 blood 235 #> 470 52.6 7 1768 1768-07-02 00:00:00 bone 235 #> 471 66.8 8 1768 1768-08-01 12:00:00 blood 236 #> 472 66.8 8 1768 1768-08-01 12:00:00 bone 236 #> 473 74.8 9 1768 1768-09-01 00:00:01 blood 237 #> 474 74.8 9 1768 1768-09-01 00:00:01 bone 237 #> 475 77.8 10 1768 1768-10-01 12:00:00 blood 238 #> 476 77.8 10 1768 1768-10-01 12:00:00 bone 238 #> 477 90.6 11 1768 1768-11-01 00:00:00 blood 239 #> 478 90.6 11 1768 1768-11-01 00:00:00 bone 239 #> 479 111.8 12 1768 1768-12-01 12:00:01 blood 240 #> 480 111.8 12 1768 1768-12-01 12:00:01 bone 240 #> 481 73.9 1 1769 1769-01-01 00:00:00 blood 241 #> 482 73.9 1 1769 1769-01-01 00:00:00 bone 241 #> 483 64.2 2 1769 1769-01-31 10:00:00 blood 242 #> 484 64.2 2 1769 1769-01-31 10:00:00 bone 242 #> 485 64.3 3 1769 1769-03-02 20:00:01 blood 243 #> 486 64.3 3 1769 1769-03-02 20:00:01 bone 243 #> 487 96.7 4 1769 1769-04-02 06:00:00 blood 244 #> 488 96.7 4 1769 1769-04-02 06:00:00 bone 244 #> 489 73.6 5 1769 1769-05-02 16:00:00 blood 245 #> 490 73.6 5 1769 1769-05-02 16:00:00 bone 245 #> 491 94.4 6 1769 1769-06-02 02:00:01 blood 246 #> 492 94.4 6 1769 1769-06-02 02:00:01 bone 246 #> 493 118.6 7 1769 1769-07-02 12:00:00 blood 247 #> 494 118.6 7 1769 1769-07-02 12:00:00 bone 247 #> 495 120.3 8 1769 1769-08-01 22:00:00 blood 248 #> 496 120.3 8 1769 1769-08-01 22:00:00 bone 248 #> 497 148.8 9 1769 1769-09-01 08:00:01 blood 249 #> 498 148.8 9 1769 1769-09-01 08:00:01 bone 249 #> 499 158.2 10 1769 1769-10-01 18:00:00 blood 250 #> 500 158.2 10 1769 1769-10-01 18:00:00 bone 250 #> 501 148.1 11 1769 1769-11-01 04:00:00 blood 251 #> 502 148.1 11 1769 1769-11-01 04:00:00 bone 251 #> 503 112.0 12 1769 1769-12-01 14:00:01 blood 252 #> 504 112.0 12 1769 1769-12-01 14:00:01 bone 252 #> 505 104.0 1 1770 1770-01-01 00:00:00 blood 253 #> 506 104.0 1 1770 1770-01-01 00:00:00 bone 253 #> 507 142.5 2 1770 1770-01-31 10:00:00 blood 254 #> 508 142.5 2 1770 1770-01-31 10:00:00 bone 254 #> 509 80.1 3 1770 1770-03-02 20:00:01 blood 255 #> 510 80.1 3 1770 1770-03-02 20:00:01 bone 255 #> 511 51.0 4 1770 1770-04-02 06:00:00 blood 256 #> 512 51.0 4 1770 1770-04-02 06:00:00 bone 256 #> 513 70.1 5 1770 1770-05-02 16:00:00 blood 257 #> 514 70.1 5 1770 1770-05-02 16:00:00 bone 257 #> 515 83.3 6 1770 1770-06-02 02:00:01 blood 258 #> 516 83.3 6 1770 1770-06-02 02:00:01 bone 258 #> 517 109.8 7 1770 1770-07-02 12:00:00 blood 259 #> 518 109.8 7 1770 1770-07-02 12:00:00 bone 259 #> 519 126.3 8 1770 1770-08-01 22:00:00 blood 260 #> 520 126.3 8 1770 1770-08-01 22:00:00 bone 260 #> 521 104.4 9 1770 1770-09-01 08:00:01 blood 261 #> 522 104.4 9 1770 1770-09-01 08:00:01 bone 261 #> 523 103.6 10 1770 1770-10-01 18:00:00 blood 262 #> 524 103.6 10 1770 1770-10-01 18:00:00 bone 262 #> 525 132.2 11 1770 1770-11-01 04:00:00 blood 263 #> 526 132.2 11 1770 1770-11-01 04:00:00 bone 263 #> 527 102.3 12 1770 1770-12-01 14:00:01 blood 264 #> 528 102.3 12 1770 1770-12-01 14:00:01 bone 264 #> 529 36.0 1 1771 1771-01-01 00:00:00 blood 265 #> 530 36.0 1 1771 1771-01-01 00:00:00 bone 265 #> 531 46.2 2 1771 1771-01-31 10:00:00 blood 266 #> 532 46.2 2 1771 1771-01-31 10:00:00 bone 266 #> 533 46.7 3 1771 1771-03-02 20:00:01 blood 267 #> 534 46.7 3 1771 1771-03-02 20:00:01 bone 267 #> 535 64.9 4 1771 1771-04-02 06:00:00 blood 268 #> 536 64.9 4 1771 1771-04-02 06:00:00 bone 268 #> 537 152.7 5 1771 1771-05-02 16:00:00 blood 269 #> 538 152.7 5 1771 1771-05-02 16:00:00 bone 269 #> 539 119.5 6 1771 1771-06-02 02:00:01 blood 270 #> 540 119.5 6 1771 1771-06-02 02:00:01 bone 270 #> 541 67.7 7 1771 1771-07-02 12:00:00 blood 271 #> 542 67.7 7 1771 1771-07-02 12:00:00 bone 271 #> 543 58.5 8 1771 1771-08-01 22:00:00 blood 272 #> 544 58.5 8 1771 1771-08-01 22:00:00 bone 272 #> 545 101.4 9 1771 1771-09-01 08:00:01 blood 273 #> 546 101.4 9 1771 1771-09-01 08:00:01 bone 273 #> 547 90.0 10 1771 1771-10-01 18:00:00 blood 274 #> 548 90.0 10 1771 1771-10-01 18:00:00 bone 274 #> 549 99.7 11 1771 1771-11-01 04:00:00 blood 275 #> 550 99.7 11 1771 1771-11-01 04:00:00 bone 275 #> 551 95.7 12 1771 1771-12-01 14:00:01 blood 276 #> 552 95.7 12 1771 1771-12-01 14:00:01 bone 276 #> 553 100.9 1 1772 1772-01-01 00:00:00 blood 277 #> 554 100.9 1 1772 1772-01-01 00:00:00 bone 277 #> 555 90.8 2 1772 1772-01-31 12:00:00 blood 278 #> 556 90.8 2 1772 1772-01-31 12:00:00 bone 278 #> 557 31.1 3 1772 1772-03-02 00:00:01 blood 279 #> 558 31.1 3 1772 1772-03-02 00:00:01 bone 279 #> 559 92.2 4 1772 1772-04-01 12:00:00 blood 280 #> 560 92.2 4 1772 1772-04-01 12:00:00 bone 280 #> 561 38.0 5 1772 1772-05-02 00:00:00 blood 281 #> 562 38.0 5 1772 1772-05-02 00:00:00 bone 281 #> 563 57.0 6 1772 1772-06-01 12:00:01 blood 282 #> 564 57.0 6 1772 1772-06-01 12:00:01 bone 282 #> 565 77.3 7 1772 1772-07-02 00:00:00 blood 283 #> 566 77.3 7 1772 1772-07-02 00:00:00 bone 283 #> 567 56.2 8 1772 1772-08-01 12:00:00 blood 284 #> 568 56.2 8 1772 1772-08-01 12:00:00 bone 284 #> 569 50.5 9 1772 1772-09-01 00:00:01 blood 285 #> 570 50.5 9 1772 1772-09-01 00:00:01 bone 285 #> 571 78.6 10 1772 1772-10-01 12:00:00 blood 286 #> 572 78.6 10 1772 1772-10-01 12:00:00 bone 286 #> 573 61.3 11 1772 1772-11-01 00:00:00 blood 287 #> 574 61.3 11 1772 1772-11-01 00:00:00 bone 287 #> 575 64.0 12 1772 1772-12-01 12:00:01 blood 288 #> 576 64.0 12 1772 1772-12-01 12:00:01 bone 288 #> 577 54.6 1 1773 1773-01-01 00:00:00 blood 289 #> 578 54.6 1 1773 1773-01-01 00:00:00 bone 289 #> 579 29.0 2 1773 1773-01-31 10:00:00 blood 290 #> 580 29.0 2 1773 1773-01-31 10:00:00 bone 290 #> 581 51.2 3 1773 1773-03-02 20:00:01 blood 291 #> 582 51.2 3 1773 1773-03-02 20:00:01 bone 291 #> 583 32.9 4 1773 1773-04-02 06:00:00 blood 292 #> 584 32.9 4 1773 1773-04-02 06:00:00 bone 292 #> 585 41.1 5 1773 1773-05-02 16:00:00 blood 293 #> 586 41.1 5 1773 1773-05-02 16:00:00 bone 293 #> 587 28.4 6 1773 1773-06-02 02:00:01 blood 294 #> 588 28.4 6 1773 1773-06-02 02:00:01 bone 294 #> 589 27.7 7 1773 1773-07-02 12:00:00 blood 295 #> 590 27.7 7 1773 1773-07-02 12:00:00 bone 295 #> 591 12.7 8 1773 1773-08-01 22:00:00 blood 296 #> 592 12.7 8 1773 1773-08-01 22:00:00 bone 296 #> 593 29.3 9 1773 1773-09-01 08:00:01 blood 297 #> 594 29.3 9 1773 1773-09-01 08:00:01 bone 297 #> 595 26.3 10 1773 1773-10-01 18:00:00 blood 298 #> 596 26.3 10 1773 1773-10-01 18:00:00 bone 298 #> 597 40.9 11 1773 1773-11-01 04:00:00 blood 299 #> 598 40.9 11 1773 1773-11-01 04:00:00 bone 299 #> 599 43.2 12 1773 1773-12-01 14:00:01 blood 300 #> 600 43.2 12 1773 1773-12-01 14:00:01 bone 300 #> 601 46.8 1 1774 1774-01-01 00:00:00 blood 301 #> 602 46.8 1 1774 1774-01-01 00:00:00 bone 301 #> 603 65.4 2 1774 1774-01-31 10:00:00 blood 302 #> 604 65.4 2 1774 1774-01-31 10:00:00 bone 302 #> 605 55.7 3 1774 1774-03-02 20:00:01 blood 303 #> 606 55.7 3 1774 1774-03-02 20:00:01 bone 303 #> 607 43.8 4 1774 1774-04-02 06:00:00 blood 304 #> 608 43.8 4 1774 1774-04-02 06:00:00 bone 304 #> 609 51.3 5 1774 1774-05-02 16:00:00 blood 305 #> 610 51.3 5 1774 1774-05-02 16:00:00 bone 305 #> 611 28.5 6 1774 1774-06-02 02:00:01 blood 306 #> 612 28.5 6 1774 1774-06-02 02:00:01 bone 306 #> 613 17.5 7 1774 1774-07-02 12:00:00 blood 307 #> 614 17.5 7 1774 1774-07-02 12:00:00 bone 307 #> 615 6.6 8 1774 1774-08-01 22:00:00 blood 308 #> 616 6.6 8 1774 1774-08-01 22:00:00 bone 308 #> 617 7.9 9 1774 1774-09-01 08:00:01 blood 309 #> 618 7.9 9 1774 1774-09-01 08:00:01 bone 309 #> 619 14.0 10 1774 1774-10-01 18:00:00 blood 310 #> 620 14.0 10 1774 1774-10-01 18:00:00 bone 310 #> 621 17.7 11 1774 1774-11-01 04:00:00 blood 311 #> 622 17.7 11 1774 1774-11-01 04:00:00 bone 311 #> 623 12.2 12 1774 1774-12-01 14:00:01 blood 312 #> 624 12.2 12 1774 1774-12-01 14:00:01 bone 312 #> 625 4.4 1 1775 1775-01-01 00:00:00 blood 313 #> 626 4.4 1 1775 1775-01-01 00:00:00 bone 313 #> 627 0.0 2 1775 1775-01-31 10:00:00 blood 314 #> 628 0.0 2 1775 1775-01-31 10:00:00 bone 314 #> 629 11.6 3 1775 1775-03-02 20:00:01 blood 315 #> 630 11.6 3 1775 1775-03-02 20:00:01 bone 315 #> 631 11.2 4 1775 1775-04-02 06:00:00 blood 316 #> 632 11.2 4 1775 1775-04-02 06:00:00 bone 316 #> 633 3.9 5 1775 1775-05-02 16:00:00 blood 317 #> 634 3.9 5 1775 1775-05-02 16:00:00 bone 317 #> 635 12.3 6 1775 1775-06-02 02:00:01 blood 318 #> 636 12.3 6 1775 1775-06-02 02:00:01 bone 318 #> 637 1.0 7 1775 1775-07-02 12:00:00 blood 319 #> 638 1.0 7 1775 1775-07-02 12:00:00 bone 319 #> 639 7.9 8 1775 1775-08-01 22:00:00 blood 320 #> 640 7.9 8 1775 1775-08-01 22:00:00 bone 320 #> 641 3.2 9 1775 1775-09-01 08:00:01 blood 321 #> 642 3.2 9 1775 1775-09-01 08:00:01 bone 321 #> 643 5.6 10 1775 1775-10-01 18:00:00 blood 322 #> 644 5.6 10 1775 1775-10-01 18:00:00 bone 322 #> 645 15.1 11 1775 1775-11-01 04:00:00 blood 323 #> 646 15.1 11 1775 1775-11-01 04:00:00 bone 323 #> 647 7.9 12 1775 1775-12-01 14:00:01 blood 324 #> 648 7.9 12 1775 1775-12-01 14:00:01 bone 324 #> 649 21.7 1 1776 1776-01-01 00:00:00 blood 325 #> 650 21.7 1 1776 1776-01-01 00:00:00 bone 325 #> 651 11.6 2 1776 1776-01-31 12:00:00 blood 326 #> 652 11.6 2 1776 1776-01-31 12:00:00 bone 326 #> 653 6.3 3 1776 1776-03-02 00:00:01 blood 327 #> 654 6.3 3 1776 1776-03-02 00:00:01 bone 327 #> 655 21.8 4 1776 1776-04-01 12:00:00 blood 328 #> 656 21.8 4 1776 1776-04-01 12:00:00 bone 328 #> 657 11.2 5 1776 1776-05-02 00:00:00 blood 329 #> 658 11.2 5 1776 1776-05-02 00:00:00 bone 329 #> 659 19.0 6 1776 1776-06-01 12:00:01 blood 330 #> 660 19.0 6 1776 1776-06-01 12:00:01 bone 330 #> 661 1.0 7 1776 1776-07-02 00:00:00 blood 331 #> 662 1.0 7 1776 1776-07-02 00:00:00 bone 331 #> 663 24.2 8 1776 1776-08-01 12:00:00 blood 332 #> 664 24.2 8 1776 1776-08-01 12:00:00 bone 332 #> 665 16.0 9 1776 1776-09-01 00:00:01 blood 333 #> 666 16.0 9 1776 1776-09-01 00:00:01 bone 333 #> 667 30.0 10 1776 1776-10-01 12:00:00 blood 334 #> 668 30.0 10 1776 1776-10-01 12:00:00 bone 334 #> 669 35.0 11 1776 1776-11-01 00:00:00 blood 335 #> 670 35.0 11 1776 1776-11-01 00:00:00 bone 335 #> 671 40.0 12 1776 1776-12-01 12:00:01 blood 336 #> 672 40.0 12 1776 1776-12-01 12:00:01 bone 336 #> 673 45.0 1 1777 1777-01-01 00:00:00 blood 337 #> 674 45.0 1 1777 1777-01-01 00:00:00 bone 337 #> 675 36.5 2 1777 1777-01-31 10:00:00 blood 338 #> 676 36.5 2 1777 1777-01-31 10:00:00 bone 338 #> 677 39.0 3 1777 1777-03-02 20:00:01 blood 339 #> 678 39.0 3 1777 1777-03-02 20:00:01 bone 339 #> 679 95.5 4 1777 1777-04-02 06:00:00 blood 340 #> 680 95.5 4 1777 1777-04-02 06:00:00 bone 340 #> 681 80.3 5 1777 1777-05-02 16:00:00 blood 341 #> 682 80.3 5 1777 1777-05-02 16:00:00 bone 341 #> 683 80.7 6 1777 1777-06-02 02:00:01 blood 342 #> 684 80.7 6 1777 1777-06-02 02:00:01 bone 342 #> 685 95.0 7 1777 1777-07-02 12:00:00 blood 343 #> 686 95.0 7 1777 1777-07-02 12:00:00 bone 343 #> 687 112.0 8 1777 1777-08-01 22:00:00 blood 344 #> 688 112.0 8 1777 1777-08-01 22:00:00 bone 344 #> 689 116.2 9 1777 1777-09-01 08:00:01 blood 345 #> 690 116.2 9 1777 1777-09-01 08:00:01 bone 345 #> 691 106.5 10 1777 1777-10-01 18:00:00 blood 346 #> 692 106.5 10 1777 1777-10-01 18:00:00 bone 346 #> 693 146.0 11 1777 1777-11-01 04:00:00 blood 347 #> 694 146.0 11 1777 1777-11-01 04:00:00 bone 347 #> 695 157.3 12 1777 1777-12-01 14:00:01 blood 348 #> 696 157.3 12 1777 1777-12-01 14:00:01 bone 348 #> 697 177.3 1 1778 1778-01-01 00:00:00 blood 349 #> 698 177.3 1 1778 1778-01-01 00:00:00 bone 349 #> 699 109.3 2 1778 1778-01-31 10:00:00 blood 350 #> 700 109.3 2 1778 1778-01-31 10:00:00 bone 350 #> 701 134.0 3 1778 1778-03-02 20:00:01 blood 351 #> 702 134.0 3 1778 1778-03-02 20:00:01 bone 351 #> 703 145.0 4 1778 1778-04-02 06:00:00 blood 352 #> 704 145.0 4 1778 1778-04-02 06:00:00 bone 352 #> 705 238.9 5 1778 1778-05-02 16:00:00 blood 353 #> 706 238.9 5 1778 1778-05-02 16:00:00 bone 353 #> 707 171.6 6 1778 1778-06-02 02:00:01 blood 354 #> 708 171.6 6 1778 1778-06-02 02:00:01 bone 354 #> 709 153.0 7 1778 1778-07-02 12:00:00 blood 355 #> 710 153.0 7 1778 1778-07-02 12:00:00 bone 355 #> 711 140.0 8 1778 1778-08-01 22:00:00 blood 356 #> 712 140.0 8 1778 1778-08-01 22:00:00 bone 356 #> 713 171.7 9 1778 1778-09-01 08:00:01 blood 357 #> 714 171.7 9 1778 1778-09-01 08:00:01 bone 357 #> 715 156.3 10 1778 1778-10-01 18:00:00 blood 358 #> 716 156.3 10 1778 1778-10-01 18:00:00 bone 358 #> 717 150.3 11 1778 1778-11-01 04:00:00 blood 359 #> 718 150.3 11 1778 1778-11-01 04:00:00 bone 359 #> 719 105.0 12 1778 1778-12-01 14:00:01 blood 360 #> 720 105.0 12 1778 1778-12-01 14:00:01 bone 360 #> 721 114.7 1 1779 1779-01-01 00:00:00 blood 361 #> 722 114.7 1 1779 1779-01-01 00:00:00 bone 361 #> 723 165.7 2 1779 1779-01-31 10:00:00 blood 362 #> 724 165.7 2 1779 1779-01-31 10:00:00 bone 362 #> 725 118.0 3 1779 1779-03-02 20:00:01 blood 363 #> 726 118.0 3 1779 1779-03-02 20:00:01 bone 363 #> 727 145.0 4 1779 1779-04-02 06:00:00 blood 364 #> 728 145.0 4 1779 1779-04-02 06:00:00 bone 364 #> 729 140.0 5 1779 1779-05-02 16:00:00 blood 365 #> 730 140.0 5 1779 1779-05-02 16:00:00 bone 365 #> 731 113.7 6 1779 1779-06-02 02:00:01 blood 366 #> 732 113.7 6 1779 1779-06-02 02:00:01 bone 366 #> 733 143.0 7 1779 1779-07-02 12:00:00 blood 367 #> 734 143.0 7 1779 1779-07-02 12:00:00 bone 367 #> 735 112.0 8 1779 1779-08-01 22:00:00 blood 368 #> 736 112.0 8 1779 1779-08-01 22:00:00 bone 368 #> 737 111.0 9 1779 1779-09-01 08:00:01 blood 369 #> 738 111.0 9 1779 1779-09-01 08:00:01 bone 369 #> 739 124.0 10 1779 1779-10-01 18:00:00 blood 370 #> 740 124.0 10 1779 1779-10-01 18:00:00 bone 370 #> 741 114.0 11 1779 1779-11-01 04:00:00 blood 371 #> 742 114.0 11 1779 1779-11-01 04:00:00 bone 371 #> 743 110.0 12 1779 1779-12-01 14:00:01 blood 372 #> 744 110.0 12 1779 1779-12-01 14:00:01 bone 372 #> 745 70.0 1 1780 1780-01-01 00:00:00 blood 373 #> 746 70.0 1 1780 1780-01-01 00:00:00 bone 373 #> 747 98.0 2 1780 1780-01-31 12:00:00 blood 374 #> 748 98.0 2 1780 1780-01-31 12:00:00 bone 374 #> 749 98.0 3 1780 1780-03-02 00:00:01 blood 375 #> 750 98.0 3 1780 1780-03-02 00:00:01 bone 375 #> 751 95.0 4 1780 1780-04-01 12:00:00 blood 376 #> 752 95.0 4 1780 1780-04-01 12:00:00 bone 376 #> 753 107.2 5 1780 1780-05-02 00:00:00 blood 377 #> 754 107.2 5 1780 1780-05-02 00:00:00 bone 377 #> 755 88.0 6 1780 1780-06-01 12:00:01 blood 378 #> 756 88.0 6 1780 1780-06-01 12:00:01 bone 378 #> 757 86.0 7 1780 1780-07-02 00:00:00 blood 379 #> 758 86.0 7 1780 1780-07-02 00:00:00 bone 379 #> 759 86.0 8 1780 1780-08-01 12:00:00 blood 380 #> 760 86.0 8 1780 1780-08-01 12:00:00 bone 380 #> 761 93.7 9 1780 1780-09-01 00:00:01 blood 381 #> 762 93.7 9 1780 1780-09-01 00:00:01 bone 381 #> 763 77.0 10 1780 1780-10-01 12:00:00 blood 382 #> 764 77.0 10 1780 1780-10-01 12:00:00 bone 382 #> 765 60.0 11 1780 1780-11-01 00:00:00 blood 383 #> 766 60.0 11 1780 1780-11-01 00:00:00 bone 383 #> 767 58.7 12 1780 1780-12-01 12:00:01 blood 384 #> 768 58.7 12 1780 1780-12-01 12:00:01 bone 384 #> 769 98.7 1 1781 1781-01-01 00:00:00 blood 385 #> 770 98.7 1 1781 1781-01-01 00:00:00 bone 385 #> 771 74.7 2 1781 1781-01-31 10:00:00 blood 386 #> 772 74.7 2 1781 1781-01-31 10:00:00 bone 386 #> 773 53.0 3 1781 1781-03-02 20:00:01 blood 387 #> 774 53.0 3 1781 1781-03-02 20:00:01 bone 387 #> 775 68.3 4 1781 1781-04-02 06:00:00 blood 388 #> 776 68.3 4 1781 1781-04-02 06:00:00 bone 388 #> 777 104.7 5 1781 1781-05-02 16:00:00 blood 389 #> 778 104.7 5 1781 1781-05-02 16:00:00 bone 389 #> 779 97.7 6 1781 1781-06-02 02:00:01 blood 390 #> 780 97.7 6 1781 1781-06-02 02:00:01 bone 390 #> 781 73.5 7 1781 1781-07-02 12:00:00 blood 391 #> 782 73.5 7 1781 1781-07-02 12:00:00 bone 391 #> 783 66.0 8 1781 1781-08-01 22:00:00 blood 392 #> 784 66.0 8 1781 1781-08-01 22:00:00 bone 392 #> 785 51.0 9 1781 1781-09-01 08:00:01 blood 393 #> 786 51.0 9 1781 1781-09-01 08:00:01 bone 393 #> 787 27.3 10 1781 1781-10-01 18:00:00 blood 394 #> 788 27.3 10 1781 1781-10-01 18:00:00 bone 394 #> 789 67.0 11 1781 1781-11-01 04:00:00 blood 395 #> 790 67.0 11 1781 1781-11-01 04:00:00 bone 395 #> 791 35.2 12 1781 1781-12-01 14:00:01 blood 396 #> 792 35.2 12 1781 1781-12-01 14:00:01 bone 396 #> 793 54.0 1 1782 1782-01-01 00:00:00 blood 397 #> 794 54.0 1 1782 1782-01-01 00:00:00 bone 397 #> 795 37.5 2 1782 1782-01-31 10:00:00 blood 398 #> 796 37.5 2 1782 1782-01-31 10:00:00 bone 398 #> 797 37.0 3 1782 1782-03-02 20:00:01 blood 399 #> 798 37.0 3 1782 1782-03-02 20:00:01 bone 399 #> 799 41.0 4 1782 1782-04-02 06:00:00 blood 400 #> 800 41.0 4 1782 1782-04-02 06:00:00 bone 400 #> 801 54.3 5 1782 1782-05-02 16:00:00 blood 401 #> 802 54.3 5 1782 1782-05-02 16:00:00 bone 401 #> 803 38.0 6 1782 1782-06-02 02:00:01 blood 402 #> 804 38.0 6 1782 1782-06-02 02:00:01 bone 402 #> 805 37.0 7 1782 1782-07-02 12:00:00 blood 403 #> 806 37.0 7 1782 1782-07-02 12:00:00 bone 403 #> 807 44.0 8 1782 1782-08-01 22:00:00 blood 404 #> 808 44.0 8 1782 1782-08-01 22:00:00 bone 404 #> 809 34.0 9 1782 1782-09-01 08:00:01 blood 405 #> 810 34.0 9 1782 1782-09-01 08:00:01 bone 405 #> 811 23.2 10 1782 1782-10-01 18:00:00 blood 406 #> 812 23.2 10 1782 1782-10-01 18:00:00 bone 406 #> 813 31.5 11 1782 1782-11-01 04:00:00 blood 407 #> 814 31.5 11 1782 1782-11-01 04:00:00 bone 407 #> 815 30.0 12 1782 1782-12-01 14:00:01 blood 408 #> 816 30.0 12 1782 1782-12-01 14:00:01 bone 408 #> 817 28.0 1 1783 1783-01-01 00:00:00 blood 409 #> 818 28.0 1 1783 1783-01-01 00:00:00 bone 409 #> 819 38.7 2 1783 1783-01-31 10:00:00 blood 410 #> 820 38.7 2 1783 1783-01-31 10:00:00 bone 410 #> 821 26.7 3 1783 1783-03-02 20:00:01 blood 411 #> 822 26.7 3 1783 1783-03-02 20:00:01 bone 411 #> 823 28.3 4 1783 1783-04-02 06:00:00 blood 412 #> 824 28.3 4 1783 1783-04-02 06:00:00 bone 412 #> 825 23.0 5 1783 1783-05-02 16:00:00 blood 413 #> 826 23.0 5 1783 1783-05-02 16:00:00 bone 413 #> 827 25.2 6 1783 1783-06-02 02:00:01 blood 414 #> 828 25.2 6 1783 1783-06-02 02:00:01 bone 414 #> 829 32.2 7 1783 1783-07-02 12:00:00 blood 415 #> 830 32.2 7 1783 1783-07-02 12:00:00 bone 415 #> 831 20.0 8 1783 1783-08-01 22:00:00 blood 416 #> 832 20.0 8 1783 1783-08-01 22:00:00 bone 416 #> 833 18.0 9 1783 1783-09-01 08:00:01 blood 417 #> 834 18.0 9 1783 1783-09-01 08:00:01 bone 417 #> 835 8.0 10 1783 1783-10-01 18:00:00 blood 418 #> 836 8.0 10 1783 1783-10-01 18:00:00 bone 418 #> 837 15.0 11 1783 1783-11-01 04:00:00 blood 419 #> 838 15.0 11 1783 1783-11-01 04:00:00 bone 419 #> 839 10.5 12 1783 1783-12-01 14:00:01 blood 420 #> 840 10.5 12 1783 1783-12-01 14:00:01 bone 420 #> 841 13.0 1 1784 1784-01-01 00:00:00 blood 421 #> 842 13.0 1 1784 1784-01-01 00:00:00 bone 421 #> 843 8.0 2 1784 1784-01-31 12:00:00 blood 422 #> 844 8.0 2 1784 1784-01-31 12:00:00 bone 422 #> 845 11.0 3 1784 1784-03-02 00:00:01 blood 423 #> 846 11.0 3 1784 1784-03-02 00:00:01 bone 423 #> 847 10.0 4 1784 1784-04-01 12:00:00 blood 424 #> 848 10.0 4 1784 1784-04-01 12:00:00 bone 424 #> 849 6.0 5 1784 1784-05-02 00:00:00 blood 425 #> 850 6.0 5 1784 1784-05-02 00:00:00 bone 425 #> 851 9.0 6 1784 1784-06-01 12:00:01 blood 426 #> 852 9.0 6 1784 1784-06-01 12:00:01 bone 426 #> 853 6.0 7 1784 1784-07-02 00:00:00 blood 427 #> 854 6.0 7 1784 1784-07-02 00:00:00 bone 427 #> 855 10.0 8 1784 1784-08-01 12:00:00 blood 428 #> 856 10.0 8 1784 1784-08-01 12:00:00 bone 428 #> 857 10.0 9 1784 1784-09-01 00:00:01 blood 429 #> 858 10.0 9 1784 1784-09-01 00:00:01 bone 429 #> 859 8.0 10 1784 1784-10-01 12:00:00 blood 430 #> 860 8.0 10 1784 1784-10-01 12:00:00 bone 430 #> 861 17.0 11 1784 1784-11-01 00:00:00 blood 431 #> 862 17.0 11 1784 1784-11-01 00:00:00 bone 431 #> 863 14.0 12 1784 1784-12-01 12:00:01 blood 432 #> 864 14.0 12 1784 1784-12-01 12:00:01 bone 432 #> 865 6.5 1 1785 1785-01-01 00:00:00 blood 433 #> 866 6.5 1 1785 1785-01-01 00:00:00 bone 433 #> 867 8.0 2 1785 1785-01-31 10:00:00 blood 434 #> 868 8.0 2 1785 1785-01-31 10:00:00 bone 434 #> 869 9.0 3 1785 1785-03-02 20:00:01 blood 435 #> 870 9.0 3 1785 1785-03-02 20:00:01 bone 435 #> 871 15.7 4 1785 1785-04-02 06:00:00 blood 436 #> 872 15.7 4 1785 1785-04-02 06:00:00 bone 436 #> 873 20.7 5 1785 1785-05-02 16:00:00 blood 437 #> 874 20.7 5 1785 1785-05-02 16:00:00 bone 437 #> 875 26.3 6 1785 1785-06-02 02:00:01 blood 438 #> 876 26.3 6 1785 1785-06-02 02:00:01 bone 438 #> 877 36.3 7 1785 1785-07-02 12:00:00 blood 439 #> 878 36.3 7 1785 1785-07-02 12:00:00 bone 439 #> 879 20.0 8 1785 1785-08-01 22:00:00 blood 440 #> 880 20.0 8 1785 1785-08-01 22:00:00 bone 440 #> 881 32.0 9 1785 1785-09-01 08:00:01 blood 441 #> 882 32.0 9 1785 1785-09-01 08:00:01 bone 441 #> 883 47.2 10 1785 1785-10-01 18:00:00 blood 442 #> 884 47.2 10 1785 1785-10-01 18:00:00 bone 442 #> 885 40.2 11 1785 1785-11-01 04:00:00 blood 443 #> 886 40.2 11 1785 1785-11-01 04:00:00 bone 443 #> 887 27.3 12 1785 1785-12-01 14:00:01 blood 444 #> 888 27.3 12 1785 1785-12-01 14:00:01 bone 444 #> 889 37.2 1 1786 1786-01-01 00:00:00 blood 445 #> 890 37.2 1 1786 1786-01-01 00:00:00 bone 445 #> 891 47.6 2 1786 1786-01-31 10:00:00 blood 446 #> 892 47.6 2 1786 1786-01-31 10:00:00 bone 446 #> 893 47.7 3 1786 1786-03-02 20:00:01 blood 447 #> 894 47.7 3 1786 1786-03-02 20:00:01 bone 447 #> 895 85.4 4 1786 1786-04-02 06:00:00 blood 448 #> 896 85.4 4 1786 1786-04-02 06:00:00 bone 448 #> 897 92.3 5 1786 1786-05-02 16:00:00 blood 449 #> 898 92.3 5 1786 1786-05-02 16:00:00 bone 449 #> 899 59.0 6 1786 1786-06-02 02:00:01 blood 450 #> 900 59.0 6 1786 1786-06-02 02:00:01 bone 450 #> 901 83.0 7 1786 1786-07-02 12:00:00 blood 451 #> 902 83.0 7 1786 1786-07-02 12:00:00 bone 451 #> 903 89.7 8 1786 1786-08-01 22:00:00 blood 452 #> 904 89.7 8 1786 1786-08-01 22:00:00 bone 452 #> 905 111.5 9 1786 1786-09-01 08:00:01 blood 453 #> 906 111.5 9 1786 1786-09-01 08:00:01 bone 453 #> 907 112.3 10 1786 1786-10-01 18:00:00 blood 454 #> 908 112.3 10 1786 1786-10-01 18:00:00 bone 454 #> 909 116.0 11 1786 1786-11-01 04:00:00 blood 455 #> 910 116.0 11 1786 1786-11-01 04:00:00 bone 455 #> 911 112.7 12 1786 1786-12-01 14:00:01 blood 456 #> 912 112.7 12 1786 1786-12-01 14:00:01 bone 456 #> 913 134.7 1 1787 1787-01-01 00:00:00 blood 457 #> 914 134.7 1 1787 1787-01-01 00:00:00 bone 457 #> 915 106.0 2 1787 1787-01-31 10:00:00 blood 458 #> 916 106.0 2 1787 1787-01-31 10:00:00 bone 458 #> 917 87.4 3 1787 1787-03-02 20:00:01 blood 459 #> 918 87.4 3 1787 1787-03-02 20:00:01 bone 459 #> 919 127.2 4 1787 1787-04-02 06:00:00 blood 460 #> 920 127.2 4 1787 1787-04-02 06:00:00 bone 460 #> 921 134.8 5 1787 1787-05-02 16:00:00 blood 461 #> 922 134.8 5 1787 1787-05-02 16:00:00 bone 461 #> 923 99.2 6 1787 1787-06-02 02:00:01 blood 462 #> 924 99.2 6 1787 1787-06-02 02:00:01 bone 462 #> 925 128.0 7 1787 1787-07-02 12:00:00 blood 463 #> 926 128.0 7 1787 1787-07-02 12:00:00 bone 463 #> 927 137.2 8 1787 1787-08-01 22:00:00 blood 464 #> 928 137.2 8 1787 1787-08-01 22:00:00 bone 464 #> 929 157.3 9 1787 1787-09-01 08:00:01 blood 465 #> 930 157.3 9 1787 1787-09-01 08:00:01 bone 465 #> 931 157.0 10 1787 1787-10-01 18:00:00 blood 466 #> 932 157.0 10 1787 1787-10-01 18:00:00 bone 466 #> 933 141.5 11 1787 1787-11-01 04:00:00 blood 467 #> 934 141.5 11 1787 1787-11-01 04:00:00 bone 467 #> 935 174.0 12 1787 1787-12-01 14:00:01 blood 468 #> 936 174.0 12 1787 1787-12-01 14:00:01 bone 468 #> 937 138.0 1 1788 1788-01-01 00:00:00 blood 469 #> 938 138.0 1 1788 1788-01-01 00:00:00 bone 469 #> 939 129.2 2 1788 1788-01-31 12:00:00 blood 470 #> 940 129.2 2 1788 1788-01-31 12:00:00 bone 470 #> 941 143.3 3 1788 1788-03-02 00:00:01 blood 471 #> 942 143.3 3 1788 1788-03-02 00:00:01 bone 471 #> 943 108.5 4 1788 1788-04-01 12:00:00 blood 472 #> 944 108.5 4 1788 1788-04-01 12:00:00 bone 472 #> 945 113.0 5 1788 1788-05-02 00:00:00 blood 473 #> 946 113.0 5 1788 1788-05-02 00:00:00 bone 473 #> 947 154.2 6 1788 1788-06-01 12:00:01 blood 474 #> 948 154.2 6 1788 1788-06-01 12:00:01 bone 474 #> 949 141.5 7 1788 1788-07-02 00:00:00 blood 475 #> 950 141.5 7 1788 1788-07-02 00:00:00 bone 475 #> 951 136.0 8 1788 1788-08-01 12:00:00 blood 476 #> 952 136.0 8 1788 1788-08-01 12:00:00 bone 476 #> 953 141.0 9 1788 1788-09-01 00:00:01 blood 477 #> 954 141.0 9 1788 1788-09-01 00:00:01 bone 477 #> 955 142.0 10 1788 1788-10-01 12:00:00 blood 478 #> 956 142.0 10 1788 1788-10-01 12:00:00 bone 478 #> 957 94.7 11 1788 1788-11-01 00:00:00 blood 479 #> 958 94.7 11 1788 1788-11-01 00:00:00 bone 479 #> 959 129.5 12 1788 1788-12-01 12:00:01 blood 480 #> 960 129.5 12 1788 1788-12-01 12:00:01 bone 480 #> 961 114.0 1 1789 1789-01-01 00:00:00 blood 481 #> 962 114.0 1 1789 1789-01-01 00:00:00 bone 481 #> 963 125.3 2 1789 1789-01-31 10:00:00 blood 482 #> 964 125.3 2 1789 1789-01-31 10:00:00 bone 482 #> 965 120.0 3 1789 1789-03-02 20:00:01 blood 483 #> 966 120.0 3 1789 1789-03-02 20:00:01 bone 483 #> 967 123.3 4 1789 1789-04-02 06:00:00 blood 484 #> 968 123.3 4 1789 1789-04-02 06:00:00 bone 484 #> 969 123.5 5 1789 1789-05-02 16:00:00 blood 485 #> 970 123.5 5 1789 1789-05-02 16:00:00 bone 485 #> 971 120.0 6 1789 1789-06-02 02:00:01 blood 486 #> 972 120.0 6 1789 1789-06-02 02:00:01 bone 486 #> 973 117.0 7 1789 1789-07-02 12:00:00 blood 487 #> 974 117.0 7 1789 1789-07-02 12:00:00 bone 487 #> 975 103.0 8 1789 1789-08-01 22:00:00 blood 488 #> 976 103.0 8 1789 1789-08-01 22:00:00 bone 488 #> 977 112.0 9 1789 1789-09-01 08:00:01 blood 489 #> 978 112.0 9 1789 1789-09-01 08:00:01 bone 489 #> 979 89.7 10 1789 1789-10-01 18:00:00 blood 490 #> 980 89.7 10 1789 1789-10-01 18:00:00 bone 490 #> 981 134.0 11 1789 1789-11-01 04:00:00 blood 491 #> 982 134.0 11 1789 1789-11-01 04:00:00 bone 491 #> 983 135.5 12 1789 1789-12-01 14:00:01 blood 492 #> 984 135.5 12 1789 1789-12-01 14:00:01 bone 492 #> 985 103.0 1 1790 1790-01-01 00:00:00 blood 493 #> 986 103.0 1 1790 1790-01-01 00:00:00 bone 493 #> 987 127.5 2 1790 1790-01-31 10:00:00 blood 494 #> 988 127.5 2 1790 1790-01-31 10:00:00 bone 494 #> 989 96.3 3 1790 1790-03-02 20:00:01 blood 495 #> 990 96.3 3 1790 1790-03-02 20:00:01 bone 495 #> 991 94.0 4 1790 1790-04-02 06:00:00 blood 496 #> 992 94.0 4 1790 1790-04-02 06:00:00 bone 496 #> 993 93.0 5 1790 1790-05-02 16:00:00 blood 497 #> 994 93.0 5 1790 1790-05-02 16:00:00 bone 497 #> 995 91.0 6 1790 1790-06-02 02:00:01 blood 498 #> 996 91.0 6 1790 1790-06-02 02:00:01 bone 498 #> 997 69.3 7 1790 1790-07-02 12:00:00 blood 499 #> 998 69.3 7 1790 1790-07-02 12:00:00 bone 499 #> 999 87.0 8 1790 1790-08-01 22:00:00 blood 500 #> 1000 87.0 8 1790 1790-08-01 22:00:00 bone 500 #> 1001 77.3 9 1790 1790-09-01 08:00:01 blood 501 #> 1002 77.3 9 1790 1790-09-01 08:00:01 bone 501 #> 1003 84.3 10 1790 1790-10-01 18:00:00 blood 502 #> 1004 84.3 10 1790 1790-10-01 18:00:00 bone 502 #> 1005 82.0 11 1790 1790-11-01 04:00:00 blood 503 #> 1006 82.0 11 1790 1790-11-01 04:00:00 bone 503 #> 1007 74.0 12 1790 1790-12-01 14:00:01 blood 504 #> 1008 74.0 12 1790 1790-12-01 14:00:01 bone 504 #> 1009 72.7 1 1791 1791-01-01 00:00:00 blood 505 #> 1010 72.7 1 1791 1791-01-01 00:00:00 bone 505 #> 1011 62.0 2 1791 1791-01-31 10:00:00 blood 506 #> 1012 62.0 2 1791 1791-01-31 10:00:00 bone 506 #> 1013 74.0 3 1791 1791-03-02 20:00:01 blood 507 #> 1014 74.0 3 1791 1791-03-02 20:00:01 bone 507 #> 1015 77.2 4 1791 1791-04-02 06:00:00 blood 508 #> 1016 77.2 4 1791 1791-04-02 06:00:00 bone 508 #> 1017 73.7 5 1791 1791-05-02 16:00:00 blood 509 #> 1018 73.7 5 1791 1791-05-02 16:00:00 bone 509 #> 1019 64.2 6 1791 1791-06-02 02:00:01 blood 510 #> 1020 64.2 6 1791 1791-06-02 02:00:01 bone 510 #> 1021 71.0 7 1791 1791-07-02 12:00:00 blood 511 #> 1022 71.0 7 1791 1791-07-02 12:00:00 bone 511 #> 1023 43.0 8 1791 1791-08-01 22:00:00 blood 512 #> 1024 43.0 8 1791 1791-08-01 22:00:00 bone 512 #> 1025 66.5 9 1791 1791-09-01 08:00:01 blood 513 #> 1026 66.5 9 1791 1791-09-01 08:00:01 bone 513 #> 1027 61.7 10 1791 1791-10-01 18:00:00 blood 514 #> 1028 61.7 10 1791 1791-10-01 18:00:00 bone 514 #> 1029 67.0 11 1791 1791-11-01 04:00:00 blood 515 #> 1030 67.0 11 1791 1791-11-01 04:00:00 bone 515 #> 1031 66.0 12 1791 1791-12-01 14:00:01 blood 516 #> 1032 66.0 12 1791 1791-12-01 14:00:01 bone 516 #> 1033 58.0 1 1792 1792-01-01 00:00:00 blood 517 #> 1034 58.0 1 1792 1792-01-01 00:00:00 bone 517 #> 1035 64.0 2 1792 1792-01-31 12:00:00 blood 518 #> 1036 64.0 2 1792 1792-01-31 12:00:00 bone 518 #> 1037 63.0 3 1792 1792-03-02 00:00:01 blood 519 #> 1038 63.0 3 1792 1792-03-02 00:00:01 bone 519 #> 1039 75.7 4 1792 1792-04-01 12:00:00 blood 520 #> 1040 75.7 4 1792 1792-04-01 12:00:00 bone 520 #> 1041 62.0 5 1792 1792-05-02 00:00:00 blood 521 #> 1042 62.0 5 1792 1792-05-02 00:00:00 bone 521 #> 1043 61.0 6 1792 1792-06-01 12:00:01 blood 522 #> 1044 61.0 6 1792 1792-06-01 12:00:01 bone 522 #> 1045 45.8 7 1792 1792-07-02 00:00:00 blood 523 #> 1046 45.8 7 1792 1792-07-02 00:00:00 bone 523 #> 1047 60.0 8 1792 1792-08-01 12:00:00 blood 524 #> 1048 60.0 8 1792 1792-08-01 12:00:00 bone 524 #> 1049 59.0 9 1792 1792-09-01 00:00:01 blood 525 #> 1050 59.0 9 1792 1792-09-01 00:00:01 bone 525 #> 1051 59.0 10 1792 1792-10-01 12:00:00 blood 526 #> 1052 59.0 10 1792 1792-10-01 12:00:00 bone 526 #> 1053 57.0 11 1792 1792-11-01 00:00:00 blood 527 #> 1054 57.0 11 1792 1792-11-01 00:00:00 bone 527 #> 1055 56.0 12 1792 1792-12-01 12:00:01 blood 528 #> 1056 56.0 12 1792 1792-12-01 12:00:01 bone 528 #> 1057 56.0 1 1793 1793-01-01 00:00:00 blood 529 #> 1058 56.0 1 1793 1793-01-01 00:00:00 bone 529 #> 1059 55.0 2 1793 1793-01-31 10:00:00 blood 530 #> 1060 55.0 2 1793 1793-01-31 10:00:00 bone 530 #> 1061 55.5 3 1793 1793-03-02 20:00:01 blood 531 #> 1062 55.5 3 1793 1793-03-02 20:00:01 bone 531 #> 1063 53.0 4 1793 1793-04-02 06:00:00 blood 532 #> 1064 53.0 4 1793 1793-04-02 06:00:00 bone 532 #> 1065 52.3 5 1793 1793-05-02 16:00:00 blood 533 #> 1066 52.3 5 1793 1793-05-02 16:00:00 bone 533 #> 1067 51.0 6 1793 1793-06-02 02:00:01 blood 534 #> 1068 51.0 6 1793 1793-06-02 02:00:01 bone 534 #> 1069 50.0 7 1793 1793-07-02 12:00:00 blood 535 #> 1070 50.0 7 1793 1793-07-02 12:00:00 bone 535 #> 1071 29.3 8 1793 1793-08-01 22:00:00 blood 536 #> 1072 29.3 8 1793 1793-08-01 22:00:00 bone 536 #> 1073 24.0 9 1793 1793-09-01 08:00:01 blood 537 #> 1074 24.0 9 1793 1793-09-01 08:00:01 bone 537 #> 1075 47.0 10 1793 1793-10-01 18:00:00 blood 538 #> 1076 47.0 10 1793 1793-10-01 18:00:00 bone 538 #> 1077 44.0 11 1793 1793-11-01 04:00:00 blood 539 #> 1078 44.0 11 1793 1793-11-01 04:00:00 bone 539 #> 1079 45.7 12 1793 1793-12-01 14:00:01 blood 540 #> 1080 45.7 12 1793 1793-12-01 14:00:01 bone 540 #> 1081 45.0 1 1794 1794-01-01 00:00:00 blood 541 #> 1082 45.0 1 1794 1794-01-01 00:00:00 bone 541 #> 1083 44.0 2 1794 1794-01-31 10:00:00 blood 542 #> 1084 44.0 2 1794 1794-01-31 10:00:00 bone 542 #> 1085 38.0 3 1794 1794-03-02 20:00:01 blood 543 #> 1086 38.0 3 1794 1794-03-02 20:00:01 bone 543 #> 1087 28.4 4 1794 1794-04-02 06:00:00 blood 544 #> 1088 28.4 4 1794 1794-04-02 06:00:00 bone 544 #> 1089 55.7 5 1794 1794-05-02 16:00:00 blood 545 #> 1090 55.7 5 1794 1794-05-02 16:00:00 bone 545 #> 1091 41.5 6 1794 1794-06-02 02:00:01 blood 546 #> 1092 41.5 6 1794 1794-06-02 02:00:01 bone 546 #> 1093 41.0 7 1794 1794-07-02 12:00:00 blood 547 #> 1094 41.0 7 1794 1794-07-02 12:00:00 bone 547 #> 1095 40.0 8 1794 1794-08-01 22:00:00 blood 548 #> 1096 40.0 8 1794 1794-08-01 22:00:00 bone 548 #> 1097 11.1 9 1794 1794-09-01 08:00:01 blood 549 #> 1098 11.1 9 1794 1794-09-01 08:00:01 bone 549 #> 1099 28.5 10 1794 1794-10-01 18:00:00 blood 550 #> 1100 28.5 10 1794 1794-10-01 18:00:00 bone 550 #> 1101 67.4 11 1794 1794-11-01 04:00:00 blood 551 #> 1102 67.4 11 1794 1794-11-01 04:00:00 bone 551 #> 1103 51.4 12 1794 1794-12-01 14:00:01 blood 552 #> 1104 51.4 12 1794 1794-12-01 14:00:01 bone 552 #> 1105 21.4 1 1795 1795-01-01 00:00:00 blood 553 #> 1106 21.4 1 1795 1795-01-01 00:00:00 bone 553 #> 1107 39.9 2 1795 1795-01-31 10:00:00 blood 554 #> 1108 39.9 2 1795 1795-01-31 10:00:00 bone 554 #> 1109 12.6 3 1795 1795-03-02 20:00:01 blood 555 #> 1110 12.6 3 1795 1795-03-02 20:00:01 bone 555 #> 1111 18.6 4 1795 1795-04-02 06:00:00 blood 556 #> 1112 18.6 4 1795 1795-04-02 06:00:00 bone 556 #> 1113 31.0 5 1795 1795-05-02 16:00:00 blood 557 #> 1114 31.0 5 1795 1795-05-02 16:00:00 bone 557 #> 1115 17.1 6 1795 1795-06-02 02:00:01 blood 558 #> 1116 17.1 6 1795 1795-06-02 02:00:01 bone 558 #> 1117 12.9 7 1795 1795-07-02 12:00:00 blood 559 #> 1118 12.9 7 1795 1795-07-02 12:00:00 bone 559 #> 1119 25.7 8 1795 1795-08-01 22:00:00 blood 560 #> 1120 25.7 8 1795 1795-08-01 22:00:00 bone 560 #> 1121 13.5 9 1795 1795-09-01 08:00:01 blood 561 #> 1122 13.5 9 1795 1795-09-01 08:00:01 bone 561 #> 1123 19.5 10 1795 1795-10-01 18:00:00 blood 562 #> 1124 19.5 10 1795 1795-10-01 18:00:00 bone 562 #> 1125 25.0 11 1795 1795-11-01 04:00:00 blood 563 #> 1126 25.0 11 1795 1795-11-01 04:00:00 bone 563 #> 1127 18.0 12 1795 1795-12-01 14:00:01 blood 564 #> 1128 18.0 12 1795 1795-12-01 14:00:01 bone 564 #> 1129 22.0 1 1796 1796-01-01 00:00:00 blood 565 #> 1130 22.0 1 1796 1796-01-01 00:00:00 bone 565 #> 1131 23.8 2 1796 1796-01-31 12:00:00 blood 566 #> 1132 23.8 2 1796 1796-01-31 12:00:00 bone 566 #> 1133 15.7 3 1796 1796-03-02 00:00:01 blood 567 #> 1134 15.7 3 1796 1796-03-02 00:00:01 bone 567 #> 1135 31.7 4 1796 1796-04-01 12:00:00 blood 568 #> 1136 31.7 4 1796 1796-04-01 12:00:00 bone 568 #> 1137 21.0 5 1796 1796-05-02 00:00:00 blood 569 #> 1138 21.0 5 1796 1796-05-02 00:00:00 bone 569 #> 1139 6.7 6 1796 1796-06-01 12:00:01 blood 570 #> 1140 6.7 6 1796 1796-06-01 12:00:01 bone 570 #> 1141 26.9 7 1796 1796-07-02 00:00:00 blood 571 #> 1142 26.9 7 1796 1796-07-02 00:00:00 bone 571 #> 1143 1.5 8 1796 1796-08-01 12:00:00 blood 572 #> 1144 1.5 8 1796 1796-08-01 12:00:00 bone 572 #> 1145 18.4 9 1796 1796-09-01 00:00:01 blood 573 #> 1146 18.4 9 1796 1796-09-01 00:00:01 bone 573 #> 1147 11.0 10 1796 1796-10-01 12:00:00 blood 574 #> 1148 11.0 10 1796 1796-10-01 12:00:00 bone 574 #> 1149 8.4 11 1796 1796-11-01 00:00:00 blood 575 #> 1150 8.4 11 1796 1796-11-01 00:00:00 bone 575 #> 1151 5.1 12 1796 1796-12-01 12:00:01 blood 576 #> 1152 5.1 12 1796 1796-12-01 12:00:01 bone 576 #> 1153 14.4 1 1797 1797-01-01 00:00:00 blood 577 #> 1154 14.4 1 1797 1797-01-01 00:00:00 bone 577 #> 1155 4.2 2 1797 1797-01-31 10:00:00 blood 578 #> 1156 4.2 2 1797 1797-01-31 10:00:00 bone 578 #> 1157 4.0 3 1797 1797-03-02 20:00:01 blood 579 #> 1158 4.0 3 1797 1797-03-02 20:00:01 bone 579 #> 1159 4.0 4 1797 1797-04-02 06:00:00 blood 580 #> 1160 4.0 4 1797 1797-04-02 06:00:00 bone 580 #> 1161 7.3 5 1797 1797-05-02 16:00:00 blood 581 #> 1162 7.3 5 1797 1797-05-02 16:00:00 bone 581 #> 1163 11.1 6 1797 1797-06-02 02:00:01 blood 582 #> 1164 11.1 6 1797 1797-06-02 02:00:01 bone 582 #> 1165 4.3 7 1797 1797-07-02 12:00:00 blood 583 #> 1166 4.3 7 1797 1797-07-02 12:00:00 bone 583 #> 1167 6.0 8 1797 1797-08-01 22:00:00 blood 584 #> 1168 6.0 8 1797 1797-08-01 22:00:00 bone 584 #> 1169 5.7 9 1797 1797-09-01 08:00:01 blood 585 #> 1170 5.7 9 1797 1797-09-01 08:00:01 bone 585 #> 1171 6.9 10 1797 1797-10-01 18:00:00 blood 586 #> 1172 6.9 10 1797 1797-10-01 18:00:00 bone 586 #> 1173 5.8 11 1797 1797-11-01 04:00:00 blood 587 #> 1174 5.8 11 1797 1797-11-01 04:00:00 bone 587 #> 1175 3.0 12 1797 1797-12-01 14:00:01 blood 588 #> 1176 3.0 12 1797 1797-12-01 14:00:01 bone 588 #> 1177 2.0 1 1798 1798-01-01 00:00:00 blood 589 #> 1178 2.0 1 1798 1798-01-01 00:00:00 bone 589 #> 1179 4.0 2 1798 1798-01-31 10:00:00 blood 590 #> 1180 4.0 2 1798 1798-01-31 10:00:00 bone 590 #> 1181 12.4 3 1798 1798-03-02 20:00:01 blood 591 #> 1182 12.4 3 1798 1798-03-02 20:00:01 bone 591 #> 1183 1.1 4 1798 1798-04-02 06:00:00 blood 592 #> 1184 1.1 4 1798 1798-04-02 06:00:00 bone 592 #> 1185 0.0 5 1798 1798-05-02 16:00:00 blood 593 #> 1186 0.0 5 1798 1798-05-02 16:00:00 bone 593 #> 1187 0.0 6 1798 1798-06-02 02:00:01 blood 594 #> 1188 0.0 6 1798 1798-06-02 02:00:01 bone 594 #> 1189 0.0 7 1798 1798-07-02 12:00:00 blood 595 #> 1190 0.0 7 1798 1798-07-02 12:00:00 bone 595 #> 1191 3.0 8 1798 1798-08-01 22:00:00 blood 596 #> 1192 3.0 8 1798 1798-08-01 22:00:00 bone 596 #> 1193 2.4 9 1798 1798-09-01 08:00:01 blood 597 #> 1194 2.4 9 1798 1798-09-01 08:00:01 bone 597 #> 1195 1.5 10 1798 1798-10-01 18:00:00 blood 598 #> 1196 1.5 10 1798 1798-10-01 18:00:00 bone 598 #> 1197 12.5 11 1798 1798-11-01 04:00:00 blood 599 #> 1198 12.5 11 1798 1798-11-01 04:00:00 bone 599 #> 1199 9.9 12 1798 1798-12-01 14:00:01 blood 600 #> 1200 9.9 12 1798 1798-12-01 14:00:01 bone 600 #> 1201 1.6 1 1799 1799-01-01 00:00:00 blood 601 #> 1202 1.6 1 1799 1799-01-01 00:00:00 bone 601 #> 1203 12.6 2 1799 1799-01-31 10:00:00 blood 602 #> 1204 12.6 2 1799 1799-01-31 10:00:00 bone 602 #> 1205 21.7 3 1799 1799-03-02 20:00:01 blood 603 #> 1206 21.7 3 1799 1799-03-02 20:00:01 bone 603 #> 1207 8.4 4 1799 1799-04-02 06:00:00 blood 604 #> 1208 8.4 4 1799 1799-04-02 06:00:00 bone 604 #> 1209 8.2 5 1799 1799-05-02 16:00:00 blood 605 #> 1210 8.2 5 1799 1799-05-02 16:00:00 bone 605 #> 1211 10.6 6 1799 1799-06-02 02:00:01 blood 606 #> 1212 10.6 6 1799 1799-06-02 02:00:01 bone 606 #> 1213 2.1 7 1799 1799-07-02 12:00:00 blood 607 #> 1214 2.1 7 1799 1799-07-02 12:00:00 bone 607 #> 1215 0.0 8 1799 1799-08-01 22:00:00 blood 608 #> 1216 0.0 8 1799 1799-08-01 22:00:00 bone 608 #> 1217 0.0 9 1799 1799-09-01 08:00:01 blood 609 #> 1218 0.0 9 1799 1799-09-01 08:00:01 bone 609 #> 1219 4.6 10 1799 1799-10-01 18:00:00 blood 610 #> 1220 4.6 10 1799 1799-10-01 18:00:00 bone 610 #> 1221 2.7 11 1799 1799-11-01 04:00:00 blood 611 #> 1222 2.7 11 1799 1799-11-01 04:00:00 bone 611 #> 1223 8.6 12 1799 1799-12-01 14:00:01 blood 612 #> 1224 8.6 12 1799 1799-12-01 14:00:01 bone 612 #> 1225 6.9 1 1800 1800-01-01 00:00:00 blood 613 #> 1226 6.9 1 1800 1800-01-01 00:00:00 bone 613 #> 1227 9.3 2 1800 1800-01-31 10:00:00 blood 614 #> 1228 9.3 2 1800 1800-01-31 10:00:00 bone 614 #> 1229 13.9 3 1800 1800-03-02 20:00:01 blood 615 #> 1230 13.9 3 1800 1800-03-02 20:00:01 bone 615 #> 1231 0.0 4 1800 1800-04-02 06:00:00 blood 616 #> 1232 0.0 4 1800 1800-04-02 06:00:00 bone 616 #> 1233 5.0 5 1800 1800-05-02 16:00:00 blood 617 #> 1234 5.0 5 1800 1800-05-02 16:00:00 bone 617 #> 1235 23.7 6 1800 1800-06-02 02:00:01 blood 618 #> 1236 23.7 6 1800 1800-06-02 02:00:01 bone 618 #> 1237 21.0 7 1800 1800-07-02 12:00:00 blood 619 #> 1238 21.0 7 1800 1800-07-02 12:00:00 bone 619 #> 1239 19.5 8 1800 1800-08-01 22:00:00 blood 620 #> 1240 19.5 8 1800 1800-08-01 22:00:00 bone 620 #> 1241 11.5 9 1800 1800-09-01 08:00:01 blood 621 #> 1242 11.5 9 1800 1800-09-01 08:00:01 bone 621 #> 1243 12.3 10 1800 1800-10-01 18:00:00 blood 622 #> 1244 12.3 10 1800 1800-10-01 18:00:00 bone 622 #> 1245 10.5 11 1800 1800-11-01 04:00:00 blood 623 #> 1246 10.5 11 1800 1800-11-01 04:00:00 bone 623 #> 1247 40.1 12 1800 1800-12-01 14:00:01 blood 624 #> 1248 40.1 12 1800 1800-12-01 14:00:01 bone 624 #> 1249 27.0 1 1801 1801-01-01 00:00:00 blood 625 #> 1250 27.0 1 1801 1801-01-01 00:00:00 bone 625 #> 1251 29.0 2 1801 1801-01-31 10:00:00 blood 626 #> 1252 29.0 2 1801 1801-01-31 10:00:00 bone 626 #> 1253 30.0 3 1801 1801-03-02 20:00:01 blood 627 #> 1254 30.0 3 1801 1801-03-02 20:00:01 bone 627 #> 1255 31.0 4 1801 1801-04-02 06:00:00 blood 628 #> 1256 31.0 4 1801 1801-04-02 06:00:00 bone 628 #> 1257 32.0 5 1801 1801-05-02 16:00:00 blood 629 #> 1258 32.0 5 1801 1801-05-02 16:00:00 bone 629 #> 1259 31.2 6 1801 1801-06-02 02:00:01 blood 630 #> 1260 31.2 6 1801 1801-06-02 02:00:01 bone 630 #> 1261 35.0 7 1801 1801-07-02 12:00:00 blood 631 #> 1262 35.0 7 1801 1801-07-02 12:00:00 bone 631 #> 1263 38.7 8 1801 1801-08-01 22:00:00 blood 632 #> 1264 38.7 8 1801 1801-08-01 22:00:00 bone 632 #> 1265 33.5 9 1801 1801-09-01 08:00:01 blood 633 #> 1266 33.5 9 1801 1801-09-01 08:00:01 bone 633 #> 1267 32.6 10 1801 1801-10-01 18:00:00 blood 634 #> 1268 32.6 10 1801 1801-10-01 18:00:00 bone 634 #> 1269 39.8 11 1801 1801-11-01 04:00:00 blood 635 #> 1270 39.8 11 1801 1801-11-01 04:00:00 bone 635 #> 1271 48.2 12 1801 1801-12-01 14:00:01 blood 636 #> 1272 48.2 12 1801 1801-12-01 14:00:01 bone 636 #> 1273 47.8 1 1802 1802-01-01 00:00:00 blood 637 #> 1274 47.8 1 1802 1802-01-01 00:00:00 bone 637 #> 1275 47.0 2 1802 1802-01-31 10:00:00 blood 638 #> 1276 47.0 2 1802 1802-01-31 10:00:00 bone 638 #> 1277 40.8 3 1802 1802-03-02 20:00:01 blood 639 #> 1278 40.8 3 1802 1802-03-02 20:00:01 bone 639 #> 1279 42.0 4 1802 1802-04-02 06:00:00 blood 640 #> 1280 42.0 4 1802 1802-04-02 06:00:00 bone 640 #> 1281 44.0 5 1802 1802-05-02 16:00:00 blood 641 #> 1282 44.0 5 1802 1802-05-02 16:00:00 bone 641 #> 1283 46.0 6 1802 1802-06-02 02:00:01 blood 642 #> 1284 46.0 6 1802 1802-06-02 02:00:01 bone 642 #> 1285 48.0 7 1802 1802-07-02 12:00:00 blood 643 #> 1286 48.0 7 1802 1802-07-02 12:00:00 bone 643 #> 1287 50.0 8 1802 1802-08-01 22:00:00 blood 644 #> 1288 50.0 8 1802 1802-08-01 22:00:00 bone 644 #> 1289 51.8 9 1802 1802-09-01 08:00:01 blood 645 #> 1290 51.8 9 1802 1802-09-01 08:00:01 bone 645 #> 1291 38.5 10 1802 1802-10-01 18:00:00 blood 646 #> 1292 38.5 10 1802 1802-10-01 18:00:00 bone 646 #> 1293 34.5 11 1802 1802-11-01 04:00:00 blood 647 #> 1294 34.5 11 1802 1802-11-01 04:00:00 bone 647 #> 1295 50.0 12 1802 1802-12-01 14:00:01 blood 648 #> 1296 50.0 12 1802 1802-12-01 14:00:01 bone 648 #> 1297 50.0 1 1803 1803-01-01 00:00:00 blood 649 #> 1298 50.0 1 1803 1803-01-01 00:00:00 bone 649 #> 1299 50.8 2 1803 1803-01-31 10:00:00 blood 650 #> 1300 50.8 2 1803 1803-01-31 10:00:00 bone 650 #> 1301 29.5 3 1803 1803-03-02 20:00:01 blood 651 #> 1302 29.5 3 1803 1803-03-02 20:00:01 bone 651 #> 1303 25.0 4 1803 1803-04-02 06:00:00 blood 652 #> 1304 25.0 4 1803 1803-04-02 06:00:00 bone 652 #> 1305 44.3 5 1803 1803-05-02 16:00:00 blood 653 #> 1306 44.3 5 1803 1803-05-02 16:00:00 bone 653 #> 1307 36.0 6 1803 1803-06-02 02:00:01 blood 654 #> 1308 36.0 6 1803 1803-06-02 02:00:01 bone 654 #> 1309 48.3 7 1803 1803-07-02 12:00:00 blood 655 #> 1310 48.3 7 1803 1803-07-02 12:00:00 bone 655 #> 1311 34.1 8 1803 1803-08-01 22:00:00 blood 656 #> 1312 34.1 8 1803 1803-08-01 22:00:00 bone 656 #> 1313 45.3 9 1803 1803-09-01 08:00:01 blood 657 #> 1314 45.3 9 1803 1803-09-01 08:00:01 bone 657 #> 1315 54.3 10 1803 1803-10-01 18:00:00 blood 658 #> 1316 54.3 10 1803 1803-10-01 18:00:00 bone 658 #> 1317 51.0 11 1803 1803-11-01 04:00:00 blood 659 #> 1318 51.0 11 1803 1803-11-01 04:00:00 bone 659 #> 1319 48.0 12 1803 1803-12-01 14:00:01 blood 660 #> 1320 48.0 12 1803 1803-12-01 14:00:01 bone 660 #> 1321 45.3 1 1804 1804-01-01 00:00:00 blood 661 #> 1322 45.3 1 1804 1804-01-01 00:00:00 bone 661 #> 1323 48.3 2 1804 1804-01-31 12:00:00 blood 662 #> 1324 48.3 2 1804 1804-01-31 12:00:00 bone 662 #> 1325 48.0 3 1804 1804-03-02 00:00:01 blood 663 #> 1326 48.0 3 1804 1804-03-02 00:00:01 bone 663 #> 1327 50.6 4 1804 1804-04-01 12:00:00 blood 664 #> 1328 50.6 4 1804 1804-04-01 12:00:00 bone 664 #> 1329 33.4 5 1804 1804-05-02 00:00:00 blood 665 #> 1330 33.4 5 1804 1804-05-02 00:00:00 bone 665 #> 1331 34.8 6 1804 1804-06-01 12:00:01 blood 666 #> 1332 34.8 6 1804 1804-06-01 12:00:01 bone 666 #> 1333 29.8 7 1804 1804-07-02 00:00:00 blood 667 #> 1334 29.8 7 1804 1804-07-02 00:00:00 bone 667 #> 1335 43.1 8 1804 1804-08-01 12:00:00 blood 668 #> 1336 43.1 8 1804 1804-08-01 12:00:00 bone 668 #> 1337 53.0 9 1804 1804-09-01 00:00:01 blood 669 #> 1338 53.0 9 1804 1804-09-01 00:00:01 bone 669 #> 1339 62.3 10 1804 1804-10-01 12:00:00 blood 670 #> 1340 62.3 10 1804 1804-10-01 12:00:00 bone 670 #> 1341 61.0 11 1804 1804-11-01 00:00:00 blood 671 #> 1342 61.0 11 1804 1804-11-01 00:00:00 bone 671 #> 1343 60.0 12 1804 1804-12-01 12:00:01 blood 672 #> 1344 60.0 12 1804 1804-12-01 12:00:01 bone 672 #> 1345 61.0 1 1805 1805-01-01 00:00:00 blood 673 #> 1346 61.0 1 1805 1805-01-01 00:00:00 bone 673 #> 1347 44.1 2 1805 1805-01-31 10:00:00 blood 674 #> 1348 44.1 2 1805 1805-01-31 10:00:00 bone 674 #> 1349 51.4 3 1805 1805-03-02 20:00:01 blood 675 #> 1350 51.4 3 1805 1805-03-02 20:00:01 bone 675 #> 1351 37.5 4 1805 1805-04-02 06:00:00 blood 676 #> 1352 37.5 4 1805 1805-04-02 06:00:00 bone 676 #> 1353 39.0 5 1805 1805-05-02 16:00:00 blood 677 #> 1354 39.0 5 1805 1805-05-02 16:00:00 bone 677 #> 1355 40.5 6 1805 1805-06-02 02:00:01 blood 678 #> 1356 40.5 6 1805 1805-06-02 02:00:01 bone 678 #> 1357 37.6 7 1805 1805-07-02 12:00:00 blood 679 #> 1358 37.6 7 1805 1805-07-02 12:00:00 bone 679 #> 1359 42.7 8 1805 1805-08-01 22:00:00 blood 680 #> 1360 42.7 8 1805 1805-08-01 22:00:00 bone 680 #> 1361 44.4 9 1805 1805-09-01 08:00:01 blood 681 #> 1362 44.4 9 1805 1805-09-01 08:00:01 bone 681 #> 1363 29.4 10 1805 1805-10-01 18:00:00 blood 682 #> 1364 29.4 10 1805 1805-10-01 18:00:00 bone 682 #> 1365 41.0 11 1805 1805-11-01 04:00:00 blood 683 #> 1366 41.0 11 1805 1805-11-01 04:00:00 bone 683 #> 1367 38.3 12 1805 1805-12-01 14:00:01 blood 684 #> 1368 38.3 12 1805 1805-12-01 14:00:01 bone 684 #> 1369 39.0 1 1806 1806-01-01 00:00:00 blood 685 #> 1370 39.0 1 1806 1806-01-01 00:00:00 bone 685 #> 1371 29.6 2 1806 1806-01-31 10:00:00 blood 686 #> 1372 29.6 2 1806 1806-01-31 10:00:00 bone 686 #> 1373 32.7 3 1806 1806-03-02 20:00:01 blood 687 #> 1374 32.7 3 1806 1806-03-02 20:00:01 bone 687 #> 1375 27.7 4 1806 1806-04-02 06:00:00 blood 688 #> 1376 27.7 4 1806 1806-04-02 06:00:00 bone 688 #> 1377 26.4 5 1806 1806-05-02 16:00:00 blood 689 #> 1378 26.4 5 1806 1806-05-02 16:00:00 bone 689 #> 1379 25.6 6 1806 1806-06-02 02:00:01 blood 690 #> 1380 25.6 6 1806 1806-06-02 02:00:01 bone 690 #> 1381 30.0 7 1806 1806-07-02 12:00:00 blood 691 #> 1382 30.0 7 1806 1806-07-02 12:00:00 bone 691 #> 1383 26.3 8 1806 1806-08-01 22:00:00 blood 692 #> 1384 26.3 8 1806 1806-08-01 22:00:00 bone 692 #> 1385 24.0 9 1806 1806-09-01 08:00:01 blood 693 #> 1386 24.0 9 1806 1806-09-01 08:00:01 bone 693 #> 1387 27.0 10 1806 1806-10-01 18:00:00 blood 694 #> 1388 27.0 10 1806 1806-10-01 18:00:00 bone 694 #> 1389 25.0 11 1806 1806-11-01 04:00:00 blood 695 #> 1390 25.0 11 1806 1806-11-01 04:00:00 bone 695 #> 1391 24.0 12 1806 1806-12-01 14:00:01 blood 696 #> 1392 24.0 12 1806 1806-12-01 14:00:01 bone 696 #> 1393 12.0 1 1807 1807-01-01 00:00:00 blood 697 #> 1394 12.0 1 1807 1807-01-01 00:00:00 bone 697 #> 1395 12.2 2 1807 1807-01-31 10:00:00 blood 698 #> 1396 12.2 2 1807 1807-01-31 10:00:00 bone 698 #> 1397 9.6 3 1807 1807-03-02 20:00:01 blood 699 #> 1398 9.6 3 1807 1807-03-02 20:00:01 bone 699 #> 1399 23.8 4 1807 1807-04-02 06:00:00 blood 700 #> 1400 23.8 4 1807 1807-04-02 06:00:00 bone 700 #> 1401 10.0 5 1807 1807-05-02 16:00:00 blood 701 #> 1402 10.0 5 1807 1807-05-02 16:00:00 bone 701 #> 1403 12.0 6 1807 1807-06-02 02:00:01 blood 702 #> 1404 12.0 6 1807 1807-06-02 02:00:01 bone 702 #> 1405 12.7 7 1807 1807-07-02 12:00:00 blood 703 #> 1406 12.7 7 1807 1807-07-02 12:00:00 bone 703 #> 1407 12.0 8 1807 1807-08-01 22:00:00 blood 704 #> 1408 12.0 8 1807 1807-08-01 22:00:00 bone 704 #> 1409 5.7 9 1807 1807-09-01 08:00:01 blood 705 #> 1410 5.7 9 1807 1807-09-01 08:00:01 bone 705 #> 1411 8.0 10 1807 1807-10-01 18:00:00 blood 706 #> 1412 8.0 10 1807 1807-10-01 18:00:00 bone 706 #> 1413 2.6 11 1807 1807-11-01 04:00:00 blood 707 #> 1414 2.6 11 1807 1807-11-01 04:00:00 bone 707 #> 1415 0.0 12 1807 1807-12-01 14:00:01 blood 708 #> 1416 0.0 12 1807 1807-12-01 14:00:01 bone 708 #> 1417 0.0 1 1808 1808-01-01 00:00:00 blood 709 #> 1418 0.0 1 1808 1808-01-01 00:00:00 bone 709 #> 1419 4.5 2 1808 1808-01-31 12:00:00 blood 710 #> 1420 4.5 2 1808 1808-01-31 12:00:00 bone 710 #> 1421 0.0 3 1808 1808-03-02 00:00:01 blood 711 #> 1422 0.0 3 1808 1808-03-02 00:00:01 bone 711 #> 1423 12.3 4 1808 1808-04-01 12:00:00 blood 712 #> 1424 12.3 4 1808 1808-04-01 12:00:00 bone 712 #> 1425 13.5 5 1808 1808-05-02 00:00:00 blood 713 #> 1426 13.5 5 1808 1808-05-02 00:00:00 bone 713 #> 1427 13.5 6 1808 1808-06-01 12:00:01 blood 714 #> 1428 13.5 6 1808 1808-06-01 12:00:01 bone 714 #> 1429 6.7 7 1808 1808-07-02 00:00:00 blood 715 #> 1430 6.7 7 1808 1808-07-02 00:00:00 bone 715 #> 1431 8.0 8 1808 1808-08-01 12:00:00 blood 716 #> 1432 8.0 8 1808 1808-08-01 12:00:00 bone 716 #> 1433 11.7 9 1808 1808-09-01 00:00:01 blood 717 #> 1434 11.7 9 1808 1808-09-01 00:00:01 bone 717 #> 1435 4.7 10 1808 1808-10-01 12:00:00 blood 718 #> 1436 4.7 10 1808 1808-10-01 12:00:00 bone 718 #> 1437 10.5 11 1808 1808-11-01 00:00:00 blood 719 #> 1438 10.5 11 1808 1808-11-01 00:00:00 bone 719 #> 1439 12.3 12 1808 1808-12-01 12:00:01 blood 720 #> 1440 12.3 12 1808 1808-12-01 12:00:01 bone 720 #> 1441 7.2 1 1809 1809-01-01 00:00:00 blood 721 #> 1442 7.2 1 1809 1809-01-01 00:00:00 bone 721 #> 1443 9.2 2 1809 1809-01-31 10:00:00 blood 722 #> 1444 9.2 2 1809 1809-01-31 10:00:00 bone 722 #> 1445 0.9 3 1809 1809-03-02 20:00:01 blood 723 #> 1446 0.9 3 1809 1809-03-02 20:00:01 bone 723 #> 1447 2.5 4 1809 1809-04-02 06:00:00 blood 724 #> 1448 2.5 4 1809 1809-04-02 06:00:00 bone 724 #> 1449 2.0 5 1809 1809-05-02 16:00:00 blood 725 #> 1450 2.0 5 1809 1809-05-02 16:00:00 bone 725 #> 1451 7.7 6 1809 1809-06-02 02:00:01 blood 726 #> 1452 7.7 6 1809 1809-06-02 02:00:01 bone 726 #> 1453 0.3 7 1809 1809-07-02 12:00:00 blood 727 #> 1454 0.3 7 1809 1809-07-02 12:00:00 bone 727 #> 1455 0.2 8 1809 1809-08-01 22:00:00 blood 728 #> 1456 0.2 8 1809 1809-08-01 22:00:00 bone 728 #> 1457 0.4 9 1809 1809-09-01 08:00:01 blood 729 #> 1458 0.4 9 1809 1809-09-01 08:00:01 bone 729 #> 1459 0.0 10 1809 1809-10-01 18:00:00 blood 730 #> 1460 0.0 10 1809 1809-10-01 18:00:00 bone 730 #> 1461 0.0 11 1809 1809-11-01 04:00:00 blood 731 #> 1462 0.0 11 1809 1809-11-01 04:00:00 bone 731 #> 1463 0.0 12 1809 1809-12-01 14:00:01 blood 732 #> 1464 0.0 12 1809 1809-12-01 14:00:01 bone 732 #> 1465 0.0 1 1810 1810-01-01 00:00:00 blood 733 #> 1466 0.0 1 1810 1810-01-01 00:00:00 bone 733 #> 1467 0.0 2 1810 1810-01-31 10:00:00 blood 734 #> 1468 0.0 2 1810 1810-01-31 10:00:00 bone 734 #> 1469 0.0 3 1810 1810-03-02 20:00:01 blood 735 #> 1470 0.0 3 1810 1810-03-02 20:00:01 bone 735 #> 1471 0.0 4 1810 1810-04-02 06:00:00 blood 736 #> 1472 0.0 4 1810 1810-04-02 06:00:00 bone 736 #> 1473 0.0 5 1810 1810-05-02 16:00:00 blood 737 #> 1474 0.0 5 1810 1810-05-02 16:00:00 bone 737 #> 1475 0.0 6 1810 1810-06-02 02:00:01 blood 738 #> 1476 0.0 6 1810 1810-06-02 02:00:01 bone 738 #> 1477 0.0 7 1810 1810-07-02 12:00:00 blood 739 #> 1478 0.0 7 1810 1810-07-02 12:00:00 bone 739 #> 1479 0.0 8 1810 1810-08-01 22:00:00 blood 740 #> 1480 0.0 8 1810 1810-08-01 22:00:00 bone 740 #> 1481 0.0 9 1810 1810-09-01 08:00:01 blood 741 #> 1482 0.0 9 1810 1810-09-01 08:00:01 bone 741 #> 1483 0.0 10 1810 1810-10-01 18:00:00 blood 742 #> 1484 0.0 10 1810 1810-10-01 18:00:00 bone 742 #> 1485 0.0 11 1810 1810-11-01 04:00:00 blood 743 #> 1486 0.0 11 1810 1810-11-01 04:00:00 bone 743 #> 1487 0.0 12 1810 1810-12-01 14:00:01 blood 744 #> 1488 0.0 12 1810 1810-12-01 14:00:01 bone 744 #> 1489 0.0 1 1811 1811-01-01 00:00:00 blood 745 #> 1490 0.0 1 1811 1811-01-01 00:00:00 bone 745 #> 1491 0.0 2 1811 1811-01-31 10:00:00 blood 746 #> 1492 0.0 2 1811 1811-01-31 10:00:00 bone 746 #> 1493 0.0 3 1811 1811-03-02 20:00:01 blood 747 #> 1494 0.0 3 1811 1811-03-02 20:00:01 bone 747 #> 1495 0.0 4 1811 1811-04-02 06:00:00 blood 748 #> 1496 0.0 4 1811 1811-04-02 06:00:00 bone 748 #> 1497 0.0 5 1811 1811-05-02 16:00:00 blood 749 #> 1498 0.0 5 1811 1811-05-02 16:00:00 bone 749 #> 1499 0.0 6 1811 1811-06-02 02:00:01 blood 750 #> 1500 0.0 6 1811 1811-06-02 02:00:01 bone 750 #> 1501 6.6 7 1811 1811-07-02 12:00:00 blood 751 #> 1502 6.6 7 1811 1811-07-02 12:00:00 bone 751 #> 1503 0.0 8 1811 1811-08-01 22:00:00 blood 752 #> 1504 0.0 8 1811 1811-08-01 22:00:00 bone 752 #> 1505 2.4 9 1811 1811-09-01 08:00:01 blood 753 #> 1506 2.4 9 1811 1811-09-01 08:00:01 bone 753 #> 1507 6.1 10 1811 1811-10-01 18:00:00 blood 754 #> 1508 6.1 10 1811 1811-10-01 18:00:00 bone 754 #> 1509 0.8 11 1811 1811-11-01 04:00:00 blood 755 #> 1510 0.8 11 1811 1811-11-01 04:00:00 bone 755 #> 1511 1.1 12 1811 1811-12-01 14:00:01 blood 756 #> 1512 1.1 12 1811 1811-12-01 14:00:01 bone 756 #> 1513 11.3 1 1812 1812-01-01 00:00:00 blood 757 #> 1514 11.3 1 1812 1812-01-01 00:00:00 bone 757 #> 1515 1.9 2 1812 1812-01-31 12:00:00 blood 758 #> 1516 1.9 2 1812 1812-01-31 12:00:00 bone 758 #> 1517 0.7 3 1812 1812-03-02 00:00:01 blood 759 #> 1518 0.7 3 1812 1812-03-02 00:00:01 bone 759 #> 1519 0.0 4 1812 1812-04-01 12:00:00 blood 760 #> 1520 0.0 4 1812 1812-04-01 12:00:00 bone 760 #> 1521 1.0 5 1812 1812-05-02 00:00:00 blood 761 #> 1522 1.0 5 1812 1812-05-02 00:00:00 bone 761 #> 1523 1.3 6 1812 1812-06-01 12:00:01 blood 762 #> 1524 1.3 6 1812 1812-06-01 12:00:01 bone 762 #> 1525 0.5 7 1812 1812-07-02 00:00:00 blood 763 #> 1526 0.5 7 1812 1812-07-02 00:00:00 bone 763 #> 1527 15.6 8 1812 1812-08-01 12:00:00 blood 764 #> 1528 15.6 8 1812 1812-08-01 12:00:00 bone 764 #> 1529 5.2 9 1812 1812-09-01 00:00:01 blood 765 #> 1530 5.2 9 1812 1812-09-01 00:00:01 bone 765 #> 1531 3.9 10 1812 1812-10-01 12:00:00 blood 766 #> 1532 3.9 10 1812 1812-10-01 12:00:00 bone 766 #> 1533 7.9 11 1812 1812-11-01 00:00:00 blood 767 #> 1534 7.9 11 1812 1812-11-01 00:00:00 bone 767 #> 1535 10.1 12 1812 1812-12-01 12:00:01 blood 768 #> 1536 10.1 12 1812 1812-12-01 12:00:01 bone 768 #> 1537 0.0 1 1813 1813-01-01 00:00:00 blood 769 #> 1538 0.0 1 1813 1813-01-01 00:00:00 bone 769 #> 1539 10.3 2 1813 1813-01-31 10:00:00 blood 770 #> 1540 10.3 2 1813 1813-01-31 10:00:00 bone 770 #> 1541 1.9 3 1813 1813-03-02 20:00:01 blood 771 #> 1542 1.9 3 1813 1813-03-02 20:00:01 bone 771 #> 1543 16.6 4 1813 1813-04-02 06:00:00 blood 772 #> 1544 16.6 4 1813 1813-04-02 06:00:00 bone 772 #> 1545 5.5 5 1813 1813-05-02 16:00:00 blood 773 #> 1546 5.5 5 1813 1813-05-02 16:00:00 bone 773 #> 1547 11.2 6 1813 1813-06-02 02:00:01 blood 774 #> 1548 11.2 6 1813 1813-06-02 02:00:01 bone 774 #> 1549 18.3 7 1813 1813-07-02 12:00:00 blood 775 #> 1550 18.3 7 1813 1813-07-02 12:00:00 bone 775 #> 1551 8.4 8 1813 1813-08-01 22:00:00 blood 776 #> 1552 8.4 8 1813 1813-08-01 22:00:00 bone 776 #> 1553 15.3 9 1813 1813-09-01 08:00:01 blood 777 #> 1554 15.3 9 1813 1813-09-01 08:00:01 bone 777 #> 1555 27.8 10 1813 1813-10-01 18:00:00 blood 778 #> 1556 27.8 10 1813 1813-10-01 18:00:00 bone 778 #> 1557 16.7 11 1813 1813-11-01 04:00:00 blood 779 #> 1558 16.7 11 1813 1813-11-01 04:00:00 bone 779 #> 1559 14.3 12 1813 1813-12-01 14:00:01 blood 780 #> 1560 14.3 12 1813 1813-12-01 14:00:01 bone 780 #> 1561 22.2 1 1814 1814-01-01 00:00:00 blood 781 #> 1562 22.2 1 1814 1814-01-01 00:00:00 bone 781 #> 1563 12.0 2 1814 1814-01-31 10:00:00 blood 782 #> 1564 12.0 2 1814 1814-01-31 10:00:00 bone 782 #> 1565 5.7 3 1814 1814-03-02 20:00:01 blood 783 #> 1566 5.7 3 1814 1814-03-02 20:00:01 bone 783 #> 1567 23.8 4 1814 1814-04-02 06:00:00 blood 784 #> 1568 23.8 4 1814 1814-04-02 06:00:00 bone 784 #> 1569 5.8 5 1814 1814-05-02 16:00:00 blood 785 #> 1570 5.8 5 1814 1814-05-02 16:00:00 bone 785 #> 1571 14.9 6 1814 1814-06-02 02:00:01 blood 786 #> 1572 14.9 6 1814 1814-06-02 02:00:01 bone 786 #> 1573 18.5 7 1814 1814-07-02 12:00:00 blood 787 #> 1574 18.5 7 1814 1814-07-02 12:00:00 bone 787 #> 1575 2.3 8 1814 1814-08-01 22:00:00 blood 788 #> 1576 2.3 8 1814 1814-08-01 22:00:00 bone 788 #> 1577 8.1 9 1814 1814-09-01 08:00:01 blood 789 #> 1578 8.1 9 1814 1814-09-01 08:00:01 bone 789 #> 1579 19.3 10 1814 1814-10-01 18:00:00 blood 790 #> 1580 19.3 10 1814 1814-10-01 18:00:00 bone 790 #> 1581 14.5 11 1814 1814-11-01 04:00:00 blood 791 #> 1582 14.5 11 1814 1814-11-01 04:00:00 bone 791 #> 1583 20.1 12 1814 1814-12-01 14:00:01 blood 792 #> 1584 20.1 12 1814 1814-12-01 14:00:01 bone 792 #> 1585 19.2 1 1815 1815-01-01 00:00:00 blood 793 #> 1586 19.2 1 1815 1815-01-01 00:00:00 bone 793 #> 1587 32.2 2 1815 1815-01-31 10:00:00 blood 794 #> 1588 32.2 2 1815 1815-01-31 10:00:00 bone 794 #> 1589 26.2 3 1815 1815-03-02 20:00:01 blood 795 #> 1590 26.2 3 1815 1815-03-02 20:00:01 bone 795 #> 1591 31.6 4 1815 1815-04-02 06:00:00 blood 796 #> 1592 31.6 4 1815 1815-04-02 06:00:00 bone 796 #> 1593 9.8 5 1815 1815-05-02 16:00:00 blood 797 #> 1594 9.8 5 1815 1815-05-02 16:00:00 bone 797 #> 1595 55.9 6 1815 1815-06-02 02:00:01 blood 798 #> 1596 55.9 6 1815 1815-06-02 02:00:01 bone 798 #> 1597 35.5 7 1815 1815-07-02 12:00:00 blood 799 #> 1598 35.5 7 1815 1815-07-02 12:00:00 bone 799 #> 1599 47.2 8 1815 1815-08-01 22:00:00 blood 800 #> 1600 47.2 8 1815 1815-08-01 22:00:00 bone 800 #> 1601 31.5 9 1815 1815-09-01 08:00:01 blood 801 #> 1602 31.5 9 1815 1815-09-01 08:00:01 bone 801 #> 1603 33.5 10 1815 1815-10-01 18:00:00 blood 802 #> 1604 33.5 10 1815 1815-10-01 18:00:00 bone 802 #> 1605 37.2 11 1815 1815-11-01 04:00:00 blood 803 #> 1606 37.2 11 1815 1815-11-01 04:00:00 bone 803 #> 1607 65.0 12 1815 1815-12-01 14:00:01 blood 804 #> 1608 65.0 12 1815 1815-12-01 14:00:01 bone 804 #> 1609 26.3 1 1816 1816-01-01 00:00:00 blood 805 #> 1610 26.3 1 1816 1816-01-01 00:00:00 bone 805 #> 1611 68.8 2 1816 1816-01-31 12:00:00 blood 806 #> 1612 68.8 2 1816 1816-01-31 12:00:00 bone 806 #> 1613 73.7 3 1816 1816-03-02 00:00:01 blood 807 #> 1614 73.7 3 1816 1816-03-02 00:00:01 bone 807 #> 1615 58.8 4 1816 1816-04-01 12:00:00 blood 808 #> 1616 58.8 4 1816 1816-04-01 12:00:00 bone 808 #> 1617 44.3 5 1816 1816-05-02 00:00:00 blood 809 #> 1618 44.3 5 1816 1816-05-02 00:00:00 bone 809 #> 1619 43.6 6 1816 1816-06-01 12:00:01 blood 810 #> 1620 43.6 6 1816 1816-06-01 12:00:01 bone 810 #> 1621 38.8 7 1816 1816-07-02 00:00:00 blood 811 #> 1622 38.8 7 1816 1816-07-02 00:00:00 bone 811 #> 1623 23.2 8 1816 1816-08-01 12:00:00 blood 812 #> 1624 23.2 8 1816 1816-08-01 12:00:00 bone 812 #> 1625 47.8 9 1816 1816-09-01 00:00:01 blood 813 #> 1626 47.8 9 1816 1816-09-01 00:00:01 bone 813 #> 1627 56.4 10 1816 1816-10-01 12:00:00 blood 814 #> 1628 56.4 10 1816 1816-10-01 12:00:00 bone 814 #> 1629 38.1 11 1816 1816-11-01 00:00:00 blood 815 #> 1630 38.1 11 1816 1816-11-01 00:00:00 bone 815 #> 1631 29.9 12 1816 1816-12-01 12:00:01 blood 816 #> 1632 29.9 12 1816 1816-12-01 12:00:01 bone 816 #> 1633 36.4 1 1817 1817-01-01 00:00:00 blood 817 #> 1634 36.4 1 1817 1817-01-01 00:00:00 bone 817 #> 1635 57.9 2 1817 1817-01-31 10:00:00 blood 818 #> 1636 57.9 2 1817 1817-01-31 10:00:00 bone 818 #> 1637 96.2 3 1817 1817-03-02 20:00:01 blood 819 #> 1638 96.2 3 1817 1817-03-02 20:00:01 bone 819 #> 1639 26.4 4 1817 1817-04-02 06:00:00 blood 820 #> 1640 26.4 4 1817 1817-04-02 06:00:00 bone 820 #> 1641 21.2 5 1817 1817-05-02 16:00:00 blood 821 #> 1642 21.2 5 1817 1817-05-02 16:00:00 bone 821 #> 1643 40.0 6 1817 1817-06-02 02:00:01 blood 822 #> 1644 40.0 6 1817 1817-06-02 02:00:01 bone 822 #> 1645 50.0 7 1817 1817-07-02 12:00:00 blood 823 #> 1646 50.0 7 1817 1817-07-02 12:00:00 bone 823 #> 1647 45.0 8 1817 1817-08-01 22:00:00 blood 824 #> 1648 45.0 8 1817 1817-08-01 22:00:00 bone 824 #> 1649 36.7 9 1817 1817-09-01 08:00:01 blood 825 #> 1650 36.7 9 1817 1817-09-01 08:00:01 bone 825 #> 1651 25.6 10 1817 1817-10-01 18:00:00 blood 826 #> 1652 25.6 10 1817 1817-10-01 18:00:00 bone 826 #> 1653 28.9 11 1817 1817-11-01 04:00:00 blood 827 #> 1654 28.9 11 1817 1817-11-01 04:00:00 bone 827 #> 1655 28.4 12 1817 1817-12-01 14:00:01 blood 828 #> 1656 28.4 12 1817 1817-12-01 14:00:01 bone 828 #> 1657 34.9 1 1818 1818-01-01 00:00:00 blood 829 #> 1658 34.9 1 1818 1818-01-01 00:00:00 bone 829 #> 1659 22.4 2 1818 1818-01-31 10:00:00 blood 830 #> 1660 22.4 2 1818 1818-01-31 10:00:00 bone 830 #> 1661 25.4 3 1818 1818-03-02 20:00:01 blood 831 #> 1662 25.4 3 1818 1818-03-02 20:00:01 bone 831 #> 1663 34.5 4 1818 1818-04-02 06:00:00 blood 832 #> 1664 34.5 4 1818 1818-04-02 06:00:00 bone 832 #> 1665 53.1 5 1818 1818-05-02 16:00:00 blood 833 #> 1666 53.1 5 1818 1818-05-02 16:00:00 bone 833 #> 1667 36.4 6 1818 1818-06-02 02:00:01 blood 834 #> 1668 36.4 6 1818 1818-06-02 02:00:01 bone 834 #> 1669 28.0 7 1818 1818-07-02 12:00:00 blood 835 #> 1670 28.0 7 1818 1818-07-02 12:00:00 bone 835 #> 1671 31.5 8 1818 1818-08-01 22:00:00 blood 836 #> 1672 31.5 8 1818 1818-08-01 22:00:00 bone 836 #> 1673 26.1 9 1818 1818-09-01 08:00:01 blood 837 #> 1674 26.1 9 1818 1818-09-01 08:00:01 bone 837 #> 1675 31.7 10 1818 1818-10-01 18:00:00 blood 838 #> 1676 31.7 10 1818 1818-10-01 18:00:00 bone 838 #> 1677 10.9 11 1818 1818-11-01 04:00:00 blood 839 #> 1678 10.9 11 1818 1818-11-01 04:00:00 bone 839 #> 1679 25.8 12 1818 1818-12-01 14:00:01 blood 840 #> 1680 25.8 12 1818 1818-12-01 14:00:01 bone 840 #> 1681 32.5 1 1819 1819-01-01 00:00:00 blood 841 #> 1682 32.5 1 1819 1819-01-01 00:00:00 bone 841 #> 1683 20.7 2 1819 1819-01-31 10:00:00 blood 842 #> 1684 20.7 2 1819 1819-01-31 10:00:00 bone 842 #> 1685 3.7 3 1819 1819-03-02 20:00:01 blood 843 #> 1686 3.7 3 1819 1819-03-02 20:00:01 bone 843 #> 1687 20.2 4 1819 1819-04-02 06:00:00 blood 844 #> 1688 20.2 4 1819 1819-04-02 06:00:00 bone 844 #> 1689 19.6 5 1819 1819-05-02 16:00:00 blood 845 #> 1690 19.6 5 1819 1819-05-02 16:00:00 bone 845 #> 1691 35.0 6 1819 1819-06-02 02:00:01 blood 846 #> 1692 35.0 6 1819 1819-06-02 02:00:01 bone 846 #> 1693 31.4 7 1819 1819-07-02 12:00:00 blood 847 #> 1694 31.4 7 1819 1819-07-02 12:00:00 bone 847 #> 1695 26.1 8 1819 1819-08-01 22:00:00 blood 848 #> 1696 26.1 8 1819 1819-08-01 22:00:00 bone 848 #> 1697 14.9 9 1819 1819-09-01 08:00:01 blood 849 #> 1698 14.9 9 1819 1819-09-01 08:00:01 bone 849 #> 1699 27.5 10 1819 1819-10-01 18:00:00 blood 850 #> 1700 27.5 10 1819 1819-10-01 18:00:00 bone 850 #> 1701 25.1 11 1819 1819-11-01 04:00:00 blood 851 #> 1702 25.1 11 1819 1819-11-01 04:00:00 bone 851 #> 1703 30.6 12 1819 1819-12-01 14:00:01 blood 852 #> 1704 30.6 12 1819 1819-12-01 14:00:01 bone 852 #> 1705 19.2 1 1820 1820-01-01 00:00:00 blood 853 #> 1706 19.2 1 1820 1820-01-01 00:00:00 bone 853 #> 1707 26.6 2 1820 1820-01-31 12:00:00 blood 854 #> 1708 26.6 2 1820 1820-01-31 12:00:00 bone 854 #> 1709 4.5 3 1820 1820-03-02 00:00:01 blood 855 #> 1710 4.5 3 1820 1820-03-02 00:00:01 bone 855 #> 1711 19.4 4 1820 1820-04-01 12:00:00 blood 856 #> 1712 19.4 4 1820 1820-04-01 12:00:00 bone 856 #> 1713 29.3 5 1820 1820-05-02 00:00:00 blood 857 #> 1714 29.3 5 1820 1820-05-02 00:00:00 bone 857 #> 1715 10.8 6 1820 1820-06-01 12:00:01 blood 858 #> 1716 10.8 6 1820 1820-06-01 12:00:01 bone 858 #> 1717 20.6 7 1820 1820-07-02 00:00:00 blood 859 #> 1718 20.6 7 1820 1820-07-02 00:00:00 bone 859 #> 1719 25.9 8 1820 1820-08-01 12:00:00 blood 860 #> 1720 25.9 8 1820 1820-08-01 12:00:00 bone 860 #> 1721 5.2 9 1820 1820-09-01 00:00:01 blood 861 #> 1722 5.2 9 1820 1820-09-01 00:00:01 bone 861 #> 1723 9.0 10 1820 1820-10-01 12:00:00 blood 862 #> 1724 9.0 10 1820 1820-10-01 12:00:00 bone 862 #> 1725 7.9 11 1820 1820-11-01 00:00:00 blood 863 #> 1726 7.9 11 1820 1820-11-01 00:00:00 bone 863 #> 1727 9.7 12 1820 1820-12-01 12:00:01 blood 864 #> 1728 9.7 12 1820 1820-12-01 12:00:01 bone 864 #> 1729 21.5 1 1821 1821-01-01 00:00:00 blood 865 #> 1730 21.5 1 1821 1821-01-01 00:00:00 bone 865 #> 1731 4.3 2 1821 1821-01-31 10:00:00 blood 866 #> 1732 4.3 2 1821 1821-01-31 10:00:00 bone 866 #> 1733 5.7 3 1821 1821-03-02 20:00:01 blood 867 #> 1734 5.7 3 1821 1821-03-02 20:00:01 bone 867 #> 1735 9.2 4 1821 1821-04-02 06:00:00 blood 868 #> 1736 9.2 4 1821 1821-04-02 06:00:00 bone 868 #> 1737 1.7 5 1821 1821-05-02 16:00:00 blood 869 #> 1738 1.7 5 1821 1821-05-02 16:00:00 bone 869 #> 1739 1.8 6 1821 1821-06-02 02:00:01 blood 870 #> 1740 1.8 6 1821 1821-06-02 02:00:01 bone 870 #> 1741 2.5 7 1821 1821-07-02 12:00:00 blood 871 #> 1742 2.5 7 1821 1821-07-02 12:00:00 bone 871 #> 1743 4.8 8 1821 1821-08-01 22:00:00 blood 872 #> 1744 4.8 8 1821 1821-08-01 22:00:00 bone 872 #> 1745 4.4 9 1821 1821-09-01 08:00:01 blood 873 #> 1746 4.4 9 1821 1821-09-01 08:00:01 bone 873 #> 1747 18.8 10 1821 1821-10-01 18:00:00 blood 874 #> 1748 18.8 10 1821 1821-10-01 18:00:00 bone 874 #> 1749 4.4 11 1821 1821-11-01 04:00:00 blood 875 #> 1750 4.4 11 1821 1821-11-01 04:00:00 bone 875 #> 1751 0.0 12 1821 1821-12-01 14:00:01 blood 876 #> 1752 0.0 12 1821 1821-12-01 14:00:01 bone 876 #> 1753 0.0 1 1822 1822-01-01 00:00:00 blood 877 #> 1754 0.0 1 1822 1822-01-01 00:00:00 bone 877 #> 1755 0.9 2 1822 1822-01-31 10:00:00 blood 878 #> 1756 0.9 2 1822 1822-01-31 10:00:00 bone 878 #> 1757 16.1 3 1822 1822-03-02 20:00:01 blood 879 #> 1758 16.1 3 1822 1822-03-02 20:00:01 bone 879 #> 1759 13.5 4 1822 1822-04-02 06:00:00 blood 880 #> 1760 13.5 4 1822 1822-04-02 06:00:00 bone 880 #> 1761 1.5 5 1822 1822-05-02 16:00:00 blood 881 #> 1762 1.5 5 1822 1822-05-02 16:00:00 bone 881 #> 1763 5.6 6 1822 1822-06-02 02:00:01 blood 882 #> 1764 5.6 6 1822 1822-06-02 02:00:01 bone 882 #> 1765 7.9 7 1822 1822-07-02 12:00:00 blood 883 #> 1766 7.9 7 1822 1822-07-02 12:00:00 bone 883 #> 1767 2.1 8 1822 1822-08-01 22:00:00 blood 884 #> 1768 2.1 8 1822 1822-08-01 22:00:00 bone 884 #> 1769 0.0 9 1822 1822-09-01 08:00:01 blood 885 #> 1770 0.0 9 1822 1822-09-01 08:00:01 bone 885 #> 1771 0.4 10 1822 1822-10-01 18:00:00 blood 886 #> 1772 0.4 10 1822 1822-10-01 18:00:00 bone 886 #> 1773 0.0 11 1822 1822-11-01 04:00:00 blood 887 #> 1774 0.0 11 1822 1822-11-01 04:00:00 bone 887 #> 1775 0.0 12 1822 1822-12-01 14:00:01 blood 888 #> 1776 0.0 12 1822 1822-12-01 14:00:01 bone 888 #> 1777 0.0 1 1823 1823-01-01 00:00:00 blood 889 #> 1778 0.0 1 1823 1823-01-01 00:00:00 bone 889 #> 1779 0.0 2 1823 1823-01-31 10:00:00 blood 890 #> 1780 0.0 2 1823 1823-01-31 10:00:00 bone 890 #> 1781 0.6 3 1823 1823-03-02 20:00:01 blood 891 #> 1782 0.6 3 1823 1823-03-02 20:00:01 bone 891 #> 1783 0.0 4 1823 1823-04-02 06:00:00 blood 892 #> 1784 0.0 4 1823 1823-04-02 06:00:00 bone 892 #> 1785 0.0 5 1823 1823-05-02 16:00:00 blood 893 #> 1786 0.0 5 1823 1823-05-02 16:00:00 bone 893 #> 1787 0.0 6 1823 1823-06-02 02:00:01 blood 894 #> 1788 0.0 6 1823 1823-06-02 02:00:01 bone 894 #> 1789 0.5 7 1823 1823-07-02 12:00:00 blood 895 #> 1790 0.5 7 1823 1823-07-02 12:00:00 bone 895 #> 1791 0.0 8 1823 1823-08-01 22:00:00 blood 896 #> 1792 0.0 8 1823 1823-08-01 22:00:00 bone 896 #> 1793 0.0 9 1823 1823-09-01 08:00:01 blood 897 #> 1794 0.0 9 1823 1823-09-01 08:00:01 bone 897 #> 1795 0.0 10 1823 1823-10-01 18:00:00 blood 898 #> 1796 0.0 10 1823 1823-10-01 18:00:00 bone 898 #> 1797 0.0 11 1823 1823-11-01 04:00:00 blood 899 #> 1798 0.0 11 1823 1823-11-01 04:00:00 bone 899 #> 1799 20.4 12 1823 1823-12-01 14:00:01 blood 900 #> 1800 20.4 12 1823 1823-12-01 14:00:01 bone 900 #> 1801 21.6 1 1824 1824-01-01 00:00:00 blood 901 #> 1802 21.6 1 1824 1824-01-01 00:00:00 bone 901 #> 1803 10.8 2 1824 1824-01-31 12:00:00 blood 902 #> 1804 10.8 2 1824 1824-01-31 12:00:00 bone 902 #> 1805 0.0 3 1824 1824-03-02 00:00:01 blood 903 #> 1806 0.0 3 1824 1824-03-02 00:00:01 bone 903 #> 1807 19.4 4 1824 1824-04-01 12:00:00 blood 904 #> 1808 19.4 4 1824 1824-04-01 12:00:00 bone 904 #> 1809 2.8 5 1824 1824-05-02 00:00:00 blood 905 #> 1810 2.8 5 1824 1824-05-02 00:00:00 bone 905 #> 1811 0.0 6 1824 1824-06-01 12:00:01 blood 906 #> 1812 0.0 6 1824 1824-06-01 12:00:01 bone 906 #> 1813 0.0 7 1824 1824-07-02 00:00:00 blood 907 #> 1814 0.0 7 1824 1824-07-02 00:00:00 bone 907 #> 1815 1.4 8 1824 1824-08-01 12:00:00 blood 908 #> 1816 1.4 8 1824 1824-08-01 12:00:00 bone 908 #> 1817 20.5 9 1824 1824-09-01 00:00:01 blood 909 #> 1818 20.5 9 1824 1824-09-01 00:00:01 bone 909 #> 1819 25.2 10 1824 1824-10-01 12:00:00 blood 910 #> 1820 25.2 10 1824 1824-10-01 12:00:00 bone 910 #> 1821 0.0 11 1824 1824-11-01 00:00:00 blood 911 #> 1822 0.0 11 1824 1824-11-01 00:00:00 bone 911 #> 1823 0.8 12 1824 1824-12-01 12:00:01 blood 912 #> 1824 0.8 12 1824 1824-12-01 12:00:01 bone 912 #> 1825 5.0 1 1825 1825-01-01 00:00:00 blood 913 #> 1826 5.0 1 1825 1825-01-01 00:00:00 bone 913 #> 1827 15.5 2 1825 1825-01-31 10:00:00 blood 914 #> 1828 15.5 2 1825 1825-01-31 10:00:00 bone 914 #> 1829 22.4 3 1825 1825-03-02 20:00:01 blood 915 #> 1830 22.4 3 1825 1825-03-02 20:00:01 bone 915 #> 1831 3.8 4 1825 1825-04-02 06:00:00 blood 916 #> 1832 3.8 4 1825 1825-04-02 06:00:00 bone 916 #> 1833 15.4 5 1825 1825-05-02 16:00:00 blood 917 #> 1834 15.4 5 1825 1825-05-02 16:00:00 bone 917 #> 1835 15.4 6 1825 1825-06-02 02:00:01 blood 918 #> 1836 15.4 6 1825 1825-06-02 02:00:01 bone 918 #> 1837 30.9 7 1825 1825-07-02 12:00:00 blood 919 #> 1838 30.9 7 1825 1825-07-02 12:00:00 bone 919 #> 1839 25.4 8 1825 1825-08-01 22:00:00 blood 920 #> 1840 25.4 8 1825 1825-08-01 22:00:00 bone 920 #> 1841 15.7 9 1825 1825-09-01 08:00:01 blood 921 #> 1842 15.7 9 1825 1825-09-01 08:00:01 bone 921 #> 1843 15.6 10 1825 1825-10-01 18:00:00 blood 922 #> 1844 15.6 10 1825 1825-10-01 18:00:00 bone 922 #> 1845 11.7 11 1825 1825-11-01 04:00:00 blood 923 #> 1846 11.7 11 1825 1825-11-01 04:00:00 bone 923 #> 1847 22.0 12 1825 1825-12-01 14:00:01 blood 924 #> 1848 22.0 12 1825 1825-12-01 14:00:01 bone 924 #> 1849 17.7 1 1826 1826-01-01 00:00:00 blood 925 #> 1850 17.7 1 1826 1826-01-01 00:00:00 bone 925 #> 1851 18.2 2 1826 1826-01-31 10:00:00 blood 926 #> 1852 18.2 2 1826 1826-01-31 10:00:00 bone 926 #> 1853 36.7 3 1826 1826-03-02 20:00:01 blood 927 #> 1854 36.7 3 1826 1826-03-02 20:00:01 bone 927 #> 1855 24.0 4 1826 1826-04-02 06:00:00 blood 928 #> 1856 24.0 4 1826 1826-04-02 06:00:00 bone 928 #> 1857 32.4 5 1826 1826-05-02 16:00:00 blood 929 #> 1858 32.4 5 1826 1826-05-02 16:00:00 bone 929 #> 1859 37.1 6 1826 1826-06-02 02:00:01 blood 930 #> 1860 37.1 6 1826 1826-06-02 02:00:01 bone 930 #> 1861 52.5 7 1826 1826-07-02 12:00:00 blood 931 #> 1862 52.5 7 1826 1826-07-02 12:00:00 bone 931 #> 1863 39.6 8 1826 1826-08-01 22:00:00 blood 932 #> 1864 39.6 8 1826 1826-08-01 22:00:00 bone 932 #> 1865 18.9 9 1826 1826-09-01 08:00:01 blood 933 #> 1866 18.9 9 1826 1826-09-01 08:00:01 bone 933 #> 1867 50.6 10 1826 1826-10-01 18:00:00 blood 934 #> 1868 50.6 10 1826 1826-10-01 18:00:00 bone 934 #> 1869 39.5 11 1826 1826-11-01 04:00:00 blood 935 #> 1870 39.5 11 1826 1826-11-01 04:00:00 bone 935 #> 1871 68.1 12 1826 1826-12-01 14:00:01 blood 936 #> 1872 68.1 12 1826 1826-12-01 14:00:01 bone 936 #> 1873 34.6 1 1827 1827-01-01 00:00:00 blood 937 #> 1874 34.6 1 1827 1827-01-01 00:00:00 bone 937 #> 1875 47.4 2 1827 1827-01-31 10:00:00 blood 938 #> 1876 47.4 2 1827 1827-01-31 10:00:00 bone 938 #> 1877 57.8 3 1827 1827-03-02 20:00:01 blood 939 #> 1878 57.8 3 1827 1827-03-02 20:00:01 bone 939 #> 1879 46.0 4 1827 1827-04-02 06:00:00 blood 940 #> 1880 46.0 4 1827 1827-04-02 06:00:00 bone 940 #> 1881 56.3 5 1827 1827-05-02 16:00:00 blood 941 #> 1882 56.3 5 1827 1827-05-02 16:00:00 bone 941 #> 1883 56.7 6 1827 1827-06-02 02:00:01 blood 942 #> 1884 56.7 6 1827 1827-06-02 02:00:01 bone 942 #> 1885 42.9 7 1827 1827-07-02 12:00:00 blood 943 #> 1886 42.9 7 1827 1827-07-02 12:00:00 bone 943 #> 1887 53.7 8 1827 1827-08-01 22:00:00 blood 944 #> 1888 53.7 8 1827 1827-08-01 22:00:00 bone 944 #> 1889 49.6 9 1827 1827-09-01 08:00:01 blood 945 #> 1890 49.6 9 1827 1827-09-01 08:00:01 bone 945 #> 1891 57.2 10 1827 1827-10-01 18:00:00 blood 946 #> 1892 57.2 10 1827 1827-10-01 18:00:00 bone 946 #> 1893 48.2 11 1827 1827-11-01 04:00:00 blood 947 #> 1894 48.2 11 1827 1827-11-01 04:00:00 bone 947 #> 1895 46.1 12 1827 1827-12-01 14:00:01 blood 948 #> 1896 46.1 12 1827 1827-12-01 14:00:01 bone 948 #> 1897 52.8 1 1828 1828-01-01 00:00:00 blood 949 #> 1898 52.8 1 1828 1828-01-01 00:00:00 bone 949 #> 1899 64.4 2 1828 1828-01-31 12:00:00 blood 950 #> 1900 64.4 2 1828 1828-01-31 12:00:00 bone 950 #> 1901 65.0 3 1828 1828-03-02 00:00:01 blood 951 #> 1902 65.0 3 1828 1828-03-02 00:00:01 bone 951 #> 1903 61.1 4 1828 1828-04-01 12:00:00 blood 952 #> 1904 61.1 4 1828 1828-04-01 12:00:00 bone 952 #> 1905 89.1 5 1828 1828-05-02 00:00:00 blood 953 #> 1906 89.1 5 1828 1828-05-02 00:00:00 bone 953 #> 1907 98.0 6 1828 1828-06-01 12:00:01 blood 954 #> 1908 98.0 6 1828 1828-06-01 12:00:01 bone 954 #> 1909 54.3 7 1828 1828-07-02 00:00:00 blood 955 #> 1910 54.3 7 1828 1828-07-02 00:00:00 bone 955 #> 1911 76.4 8 1828 1828-08-01 12:00:00 blood 956 #> 1912 76.4 8 1828 1828-08-01 12:00:00 bone 956 #> 1913 50.4 9 1828 1828-09-01 00:00:01 blood 957 #> 1914 50.4 9 1828 1828-09-01 00:00:01 bone 957 #> 1915 54.7 10 1828 1828-10-01 12:00:00 blood 958 #> 1916 54.7 10 1828 1828-10-01 12:00:00 bone 958 #> 1917 57.0 11 1828 1828-11-01 00:00:00 blood 959 #> 1918 57.0 11 1828 1828-11-01 00:00:00 bone 959 #> 1919 46.6 12 1828 1828-12-01 12:00:01 blood 960 #> 1920 46.6 12 1828 1828-12-01 12:00:01 bone 960 #> 1921 43.0 1 1829 1829-01-01 00:00:00 blood 961 #> 1922 43.0 1 1829 1829-01-01 00:00:00 bone 961 #> 1923 49.4 2 1829 1829-01-31 10:00:00 blood 962 #> 1924 49.4 2 1829 1829-01-31 10:00:00 bone 962 #> 1925 72.3 3 1829 1829-03-02 20:00:01 blood 963 #> 1926 72.3 3 1829 1829-03-02 20:00:01 bone 963 #> 1927 95.0 4 1829 1829-04-02 06:00:00 blood 964 #> 1928 95.0 4 1829 1829-04-02 06:00:00 bone 964 #> 1929 67.5 5 1829 1829-05-02 16:00:00 blood 965 #> 1930 67.5 5 1829 1829-05-02 16:00:00 bone 965 #> 1931 73.9 6 1829 1829-06-02 02:00:01 blood 966 #> 1932 73.9 6 1829 1829-06-02 02:00:01 bone 966 #> 1933 90.8 7 1829 1829-07-02 12:00:00 blood 967 #> 1934 90.8 7 1829 1829-07-02 12:00:00 bone 967 #> 1935 78.3 8 1829 1829-08-01 22:00:00 blood 968 #> 1936 78.3 8 1829 1829-08-01 22:00:00 bone 968 #> 1937 52.8 9 1829 1829-09-01 08:00:01 blood 969 #> 1938 52.8 9 1829 1829-09-01 08:00:01 bone 969 #> 1939 57.2 10 1829 1829-10-01 18:00:00 blood 970 #> 1940 57.2 10 1829 1829-10-01 18:00:00 bone 970 #> 1941 67.6 11 1829 1829-11-01 04:00:00 blood 971 #> 1942 67.6 11 1829 1829-11-01 04:00:00 bone 971 #> 1943 56.5 12 1829 1829-12-01 14:00:01 blood 972 #> 1944 56.5 12 1829 1829-12-01 14:00:01 bone 972 #> 1945 52.2 1 1830 1830-01-01 00:00:00 blood 973 #> 1946 52.2 1 1830 1830-01-01 00:00:00 bone 973 #> 1947 72.1 2 1830 1830-01-31 10:00:00 blood 974 #> 1948 72.1 2 1830 1830-01-31 10:00:00 bone 974 #> 1949 84.6 3 1830 1830-03-02 20:00:01 blood 975 #> 1950 84.6 3 1830 1830-03-02 20:00:01 bone 975 #> 1951 107.1 4 1830 1830-04-02 06:00:00 blood 976 #> 1952 107.1 4 1830 1830-04-02 06:00:00 bone 976 #> 1953 66.3 5 1830 1830-05-02 16:00:00 blood 977 #> 1954 66.3 5 1830 1830-05-02 16:00:00 bone 977 #> 1955 65.1 6 1830 1830-06-02 02:00:01 blood 978 #> 1956 65.1 6 1830 1830-06-02 02:00:01 bone 978 #> 1957 43.9 7 1830 1830-07-02 12:00:00 blood 979 #> 1958 43.9 7 1830 1830-07-02 12:00:00 bone 979 #> 1959 50.7 8 1830 1830-08-01 22:00:00 blood 980 #> 1960 50.7 8 1830 1830-08-01 22:00:00 bone 980 #> 1961 62.1 9 1830 1830-09-01 08:00:01 blood 981 #> 1962 62.1 9 1830 1830-09-01 08:00:01 bone 981 #> 1963 84.4 10 1830 1830-10-01 18:00:00 blood 982 #> 1964 84.4 10 1830 1830-10-01 18:00:00 bone 982 #> 1965 81.2 11 1830 1830-11-01 04:00:00 blood 983 #> 1966 81.2 11 1830 1830-11-01 04:00:00 bone 983 #> 1967 82.1 12 1830 1830-12-01 14:00:01 blood 984 #> 1968 82.1 12 1830 1830-12-01 14:00:01 bone 984 #> 1969 47.5 1 1831 1831-01-01 00:00:00 blood 985 #> 1970 47.5 1 1831 1831-01-01 00:00:00 bone 985 #> 1971 50.1 2 1831 1831-01-31 10:00:00 blood 986 #> 1972 50.1 2 1831 1831-01-31 10:00:00 bone 986 #> 1973 93.4 3 1831 1831-03-02 20:00:01 blood 987 #> 1974 93.4 3 1831 1831-03-02 20:00:01 bone 987 #> 1975 54.6 4 1831 1831-04-02 06:00:00 blood 988 #> 1976 54.6 4 1831 1831-04-02 06:00:00 bone 988 #> 1977 38.1 5 1831 1831-05-02 16:00:00 blood 989 #> 1978 38.1 5 1831 1831-05-02 16:00:00 bone 989 #> 1979 33.4 6 1831 1831-06-02 02:00:01 blood 990 #> 1980 33.4 6 1831 1831-06-02 02:00:01 bone 990 #> 1981 45.2 7 1831 1831-07-02 12:00:00 blood 991 #> 1982 45.2 7 1831 1831-07-02 12:00:00 bone 991 #> 1983 54.9 8 1831 1831-08-01 22:00:00 blood 992 #> 1984 54.9 8 1831 1831-08-01 22:00:00 bone 992 #> 1985 37.9 9 1831 1831-09-01 08:00:01 blood 993 #> 1986 37.9 9 1831 1831-09-01 08:00:01 bone 993 #> 1987 46.2 10 1831 1831-10-01 18:00:00 blood 994 #> 1988 46.2 10 1831 1831-10-01 18:00:00 bone 994 #> 1989 43.5 11 1831 1831-11-01 04:00:00 blood 995 #> 1990 43.5 11 1831 1831-11-01 04:00:00 bone 995 #> 1991 28.9 12 1831 1831-12-01 14:00:01 blood 996 #> 1992 28.9 12 1831 1831-12-01 14:00:01 bone 996 #> 1993 30.9 1 1832 1832-01-01 00:00:00 blood 997 #> 1994 30.9 1 1832 1832-01-01 00:00:00 bone 997 #> 1995 55.5 2 1832 1832-01-31 12:00:00 blood 998 #> 1996 55.5 2 1832 1832-01-31 12:00:00 bone 998 #> 1997 55.1 3 1832 1832-03-02 00:00:01 blood 999 #> 1998 55.1 3 1832 1832-03-02 00:00:01 bone 999 #> 1999 26.9 4 1832 1832-04-01 12:00:00 blood 1000 #> 2000 26.9 4 1832 1832-04-01 12:00:00 bone 1000 #> 2001 41.3 5 1832 1832-05-02 00:00:00 blood 1001 #> 2002 41.3 5 1832 1832-05-02 00:00:00 bone 1001 #> 2003 26.7 6 1832 1832-06-01 12:00:01 blood 1002 #> 2004 26.7 6 1832 1832-06-01 12:00:01 bone 1002 #> 2005 13.9 7 1832 1832-07-02 00:00:00 blood 1003 #> 2006 13.9 7 1832 1832-07-02 00:00:00 bone 1003 #> 2007 8.9 8 1832 1832-08-01 12:00:00 blood 1004 #> 2008 8.9 8 1832 1832-08-01 12:00:00 bone 1004 #> 2009 8.2 9 1832 1832-09-01 00:00:01 blood 1005 #> 2010 8.2 9 1832 1832-09-01 00:00:01 bone 1005 #> 2011 21.1 10 1832 1832-10-01 12:00:00 blood 1006 #> 2012 21.1 10 1832 1832-10-01 12:00:00 bone 1006 #> 2013 14.3 11 1832 1832-11-01 00:00:00 blood 1007 #> 2014 14.3 11 1832 1832-11-01 00:00:00 bone 1007 #> 2015 27.5 12 1832 1832-12-01 12:00:01 blood 1008 #> 2016 27.5 12 1832 1832-12-01 12:00:01 bone 1008 #> 2017 11.3 1 1833 1833-01-01 00:00:00 blood 1009 #> 2018 11.3 1 1833 1833-01-01 00:00:00 bone 1009 #> 2019 14.9 2 1833 1833-01-31 10:00:00 blood 1010 #> 2020 14.9 2 1833 1833-01-31 10:00:00 bone 1010 #> 2021 11.8 3 1833 1833-03-02 20:00:01 blood 1011 #> 2022 11.8 3 1833 1833-03-02 20:00:01 bone 1011 #> 2023 2.8 4 1833 1833-04-02 06:00:00 blood 1012 #> 2024 2.8 4 1833 1833-04-02 06:00:00 bone 1012 #> 2025 12.9 5 1833 1833-05-02 16:00:00 blood 1013 #> 2026 12.9 5 1833 1833-05-02 16:00:00 bone 1013 #> 2027 1.0 6 1833 1833-06-02 02:00:01 blood 1014 #> 2028 1.0 6 1833 1833-06-02 02:00:01 bone 1014 #> 2029 7.0 7 1833 1833-07-02 12:00:00 blood 1015 #> 2030 7.0 7 1833 1833-07-02 12:00:00 bone 1015 #> 2031 5.7 8 1833 1833-08-01 22:00:00 blood 1016 #> 2032 5.7 8 1833 1833-08-01 22:00:00 bone 1016 #> 2033 11.6 9 1833 1833-09-01 08:00:01 blood 1017 #> 2034 11.6 9 1833 1833-09-01 08:00:01 bone 1017 #> 2035 7.5 10 1833 1833-10-01 18:00:00 blood 1018 #> 2036 7.5 10 1833 1833-10-01 18:00:00 bone 1018 #> 2037 5.9 11 1833 1833-11-01 04:00:00 blood 1019 #> 2038 5.9 11 1833 1833-11-01 04:00:00 bone 1019 #> 2039 9.9 12 1833 1833-12-01 14:00:01 blood 1020 #> 2040 9.9 12 1833 1833-12-01 14:00:01 bone 1020 #> 2041 4.9 1 1834 1834-01-01 00:00:00 blood 1021 #> 2042 4.9 1 1834 1834-01-01 00:00:00 bone 1021 #> 2043 18.1 2 1834 1834-01-31 10:00:00 blood 1022 #> 2044 18.1 2 1834 1834-01-31 10:00:00 bone 1022 #> 2045 3.9 3 1834 1834-03-02 20:00:01 blood 1023 #> 2046 3.9 3 1834 1834-03-02 20:00:01 bone 1023 #> 2047 1.4 4 1834 1834-04-02 06:00:00 blood 1024 #> 2048 1.4 4 1834 1834-04-02 06:00:00 bone 1024 #> 2049 8.8 5 1834 1834-05-02 16:00:00 blood 1025 #> 2050 8.8 5 1834 1834-05-02 16:00:00 bone 1025 #> 2051 7.8 6 1834 1834-06-02 02:00:01 blood 1026 #> 2052 7.8 6 1834 1834-06-02 02:00:01 bone 1026 #> 2053 8.7 7 1834 1834-07-02 12:00:00 blood 1027 #> 2054 8.7 7 1834 1834-07-02 12:00:00 bone 1027 #> 2055 4.0 8 1834 1834-08-01 22:00:00 blood 1028 #> 2056 4.0 8 1834 1834-08-01 22:00:00 bone 1028 #> 2057 11.5 9 1834 1834-09-01 08:00:01 blood 1029 #> 2058 11.5 9 1834 1834-09-01 08:00:01 bone 1029 #> 2059 24.8 10 1834 1834-10-01 18:00:00 blood 1030 #> 2060 24.8 10 1834 1834-10-01 18:00:00 bone 1030 #> 2061 30.5 11 1834 1834-11-01 04:00:00 blood 1031 #> 2062 30.5 11 1834 1834-11-01 04:00:00 bone 1031 #> 2063 34.5 12 1834 1834-12-01 14:00:01 blood 1032 #> 2064 34.5 12 1834 1834-12-01 14:00:01 bone 1032 #> 2065 7.5 1 1835 1835-01-01 00:00:00 blood 1033 #> 2066 7.5 1 1835 1835-01-01 00:00:00 bone 1033 #> 2067 24.5 2 1835 1835-01-31 10:00:00 blood 1034 #> 2068 24.5 2 1835 1835-01-31 10:00:00 bone 1034 #> 2069 19.7 3 1835 1835-03-02 20:00:01 blood 1035 #> 2070 19.7 3 1835 1835-03-02 20:00:01 bone 1035 #> 2071 61.5 4 1835 1835-04-02 06:00:00 blood 1036 #> 2072 61.5 4 1835 1835-04-02 06:00:00 bone 1036 #> 2073 43.6 5 1835 1835-05-02 16:00:00 blood 1037 #> 2074 43.6 5 1835 1835-05-02 16:00:00 bone 1037 #> 2075 33.2 6 1835 1835-06-02 02:00:01 blood 1038 #> 2076 33.2 6 1835 1835-06-02 02:00:01 bone 1038 #> 2077 59.8 7 1835 1835-07-02 12:00:00 blood 1039 #> 2078 59.8 7 1835 1835-07-02 12:00:00 bone 1039 #> 2079 59.0 8 1835 1835-08-01 22:00:00 blood 1040 #> 2080 59.0 8 1835 1835-08-01 22:00:00 bone 1040 #> 2081 100.8 9 1835 1835-09-01 08:00:01 blood 1041 #> 2082 100.8 9 1835 1835-09-01 08:00:01 bone 1041 #> 2083 95.2 10 1835 1835-10-01 18:00:00 blood 1042 #> 2084 95.2 10 1835 1835-10-01 18:00:00 bone 1042 #> 2085 100.0 11 1835 1835-11-01 04:00:00 blood 1043 #> 2086 100.0 11 1835 1835-11-01 04:00:00 bone 1043 #> 2087 77.5 12 1835 1835-12-01 14:00:01 blood 1044 #> 2088 77.5 12 1835 1835-12-01 14:00:01 bone 1044 #> 2089 88.6 1 1836 1836-01-01 00:00:00 blood 1045 #> 2090 88.6 1 1836 1836-01-01 00:00:00 bone 1045 #> 2091 107.6 2 1836 1836-01-31 12:00:00 blood 1046 #> 2092 107.6 2 1836 1836-01-31 12:00:00 bone 1046 #> 2093 98.1 3 1836 1836-03-02 00:00:01 blood 1047 #> 2094 98.1 3 1836 1836-03-02 00:00:01 bone 1047 #> 2095 142.9 4 1836 1836-04-01 12:00:00 blood 1048 #> 2096 142.9 4 1836 1836-04-01 12:00:00 bone 1048 #> 2097 111.4 5 1836 1836-05-02 00:00:00 blood 1049 #> 2098 111.4 5 1836 1836-05-02 00:00:00 bone 1049 #> 2099 124.7 6 1836 1836-06-01 12:00:01 blood 1050 #> 2100 124.7 6 1836 1836-06-01 12:00:01 bone 1050 #> 2101 116.7 7 1836 1836-07-02 00:00:00 blood 1051 #> 2102 116.7 7 1836 1836-07-02 00:00:00 bone 1051 #> 2103 107.8 8 1836 1836-08-01 12:00:00 blood 1052 #> 2104 107.8 8 1836 1836-08-01 12:00:00 bone 1052 #> 2105 95.1 9 1836 1836-09-01 00:00:01 blood 1053 #> 2106 95.1 9 1836 1836-09-01 00:00:01 bone 1053 #> 2107 137.4 10 1836 1836-10-01 12:00:00 blood 1054 #> 2108 137.4 10 1836 1836-10-01 12:00:00 bone 1054 #> 2109 120.9 11 1836 1836-11-01 00:00:00 blood 1055 #> 2110 120.9 11 1836 1836-11-01 00:00:00 bone 1055 #> 2111 206.2 12 1836 1836-12-01 12:00:01 blood 1056 #> 2112 206.2 12 1836 1836-12-01 12:00:01 bone 1056 #> 2113 188.0 1 1837 1837-01-01 00:00:00 blood 1057 #> 2114 188.0 1 1837 1837-01-01 00:00:00 bone 1057 #> 2115 175.6 2 1837 1837-01-31 10:00:00 blood 1058 #> 2116 175.6 2 1837 1837-01-31 10:00:00 bone 1058 #> 2117 134.6 3 1837 1837-03-02 20:00:01 blood 1059 #> 2118 134.6 3 1837 1837-03-02 20:00:01 bone 1059 #> 2119 138.2 4 1837 1837-04-02 06:00:00 blood 1060 #> 2120 138.2 4 1837 1837-04-02 06:00:00 bone 1060 #> 2121 111.3 5 1837 1837-05-02 16:00:00 blood 1061 #> 2122 111.3 5 1837 1837-05-02 16:00:00 bone 1061 #> 2123 158.0 6 1837 1837-06-02 02:00:01 blood 1062 #> 2124 158.0 6 1837 1837-06-02 02:00:01 bone 1062 #> 2125 162.8 7 1837 1837-07-02 12:00:00 blood 1063 #> 2126 162.8 7 1837 1837-07-02 12:00:00 bone 1063 #> 2127 134.0 8 1837 1837-08-01 22:00:00 blood 1064 #> 2128 134.0 8 1837 1837-08-01 22:00:00 bone 1064 #> 2129 96.3 9 1837 1837-09-01 08:00:01 blood 1065 #> 2130 96.3 9 1837 1837-09-01 08:00:01 bone 1065 #> 2131 123.7 10 1837 1837-10-01 18:00:00 blood 1066 #> 2132 123.7 10 1837 1837-10-01 18:00:00 bone 1066 #> 2133 107.0 11 1837 1837-11-01 04:00:00 blood 1067 #> 2134 107.0 11 1837 1837-11-01 04:00:00 bone 1067 #> 2135 129.8 12 1837 1837-12-01 14:00:01 blood 1068 #> 2136 129.8 12 1837 1837-12-01 14:00:01 bone 1068 #> 2137 144.9 1 1838 1838-01-01 00:00:00 blood 1069 #> 2138 144.9 1 1838 1838-01-01 00:00:00 bone 1069 #> 2139 84.8 2 1838 1838-01-31 10:00:00 blood 1070 #> 2140 84.8 2 1838 1838-01-31 10:00:00 bone 1070 #> 2141 140.8 3 1838 1838-03-02 20:00:01 blood 1071 #> 2142 140.8 3 1838 1838-03-02 20:00:01 bone 1071 #> 2143 126.6 4 1838 1838-04-02 06:00:00 blood 1072 #> 2144 126.6 4 1838 1838-04-02 06:00:00 bone 1072 #> 2145 137.6 5 1838 1838-05-02 16:00:00 blood 1073 #> 2146 137.6 5 1838 1838-05-02 16:00:00 bone 1073 #> 2147 94.5 6 1838 1838-06-02 02:00:01 blood 1074 #> 2148 94.5 6 1838 1838-06-02 02:00:01 bone 1074 #> 2149 108.2 7 1838 1838-07-02 12:00:00 blood 1075 #> 2150 108.2 7 1838 1838-07-02 12:00:00 bone 1075 #> 2151 78.8 8 1838 1838-08-01 22:00:00 blood 1076 #> 2152 78.8 8 1838 1838-08-01 22:00:00 bone 1076 #> 2153 73.6 9 1838 1838-09-01 08:00:01 blood 1077 #> 2154 73.6 9 1838 1838-09-01 08:00:01 bone 1077 #> 2155 90.8 10 1838 1838-10-01 18:00:00 blood 1078 #> 2156 90.8 10 1838 1838-10-01 18:00:00 bone 1078 #> 2157 77.4 11 1838 1838-11-01 04:00:00 blood 1079 #> 2158 77.4 11 1838 1838-11-01 04:00:00 bone 1079 #> 2159 79.8 12 1838 1838-12-01 14:00:01 blood 1080 #> 2160 79.8 12 1838 1838-12-01 14:00:01 bone 1080 #> 2161 107.6 1 1839 1839-01-01 00:00:00 blood 1081 #> 2162 107.6 1 1839 1839-01-01 00:00:00 bone 1081 #> 2163 102.5 2 1839 1839-01-31 10:00:00 blood 1082 #> 2164 102.5 2 1839 1839-01-31 10:00:00 bone 1082 #> 2165 77.7 3 1839 1839-03-02 20:00:01 blood 1083 #> 2166 77.7 3 1839 1839-03-02 20:00:01 bone 1083 #> 2167 61.8 4 1839 1839-04-02 06:00:00 blood 1084 #> 2168 61.8 4 1839 1839-04-02 06:00:00 bone 1084 #> 2169 53.8 5 1839 1839-05-02 16:00:00 blood 1085 #> 2170 53.8 5 1839 1839-05-02 16:00:00 bone 1085 #> 2171 54.6 6 1839 1839-06-02 02:00:01 blood 1086 #> 2172 54.6 6 1839 1839-06-02 02:00:01 bone 1086 #> 2173 84.7 7 1839 1839-07-02 12:00:00 blood 1087 #> 2174 84.7 7 1839 1839-07-02 12:00:00 bone 1087 #> 2175 131.2 8 1839 1839-08-01 22:00:00 blood 1088 #> 2176 131.2 8 1839 1839-08-01 22:00:00 bone 1088 #> 2177 132.7 9 1839 1839-09-01 08:00:01 blood 1089 #> 2178 132.7 9 1839 1839-09-01 08:00:01 bone 1089 #> 2179 90.8 10 1839 1839-10-01 18:00:00 blood 1090 #> 2180 90.8 10 1839 1839-10-01 18:00:00 bone 1090 #> 2181 68.8 11 1839 1839-11-01 04:00:00 blood 1091 #> 2182 68.8 11 1839 1839-11-01 04:00:00 bone 1091 #> 2183 63.6 12 1839 1839-12-01 14:00:01 blood 1092 #> 2184 63.6 12 1839 1839-12-01 14:00:01 bone 1092 #> 2185 81.2 1 1840 1840-01-01 00:00:00 blood 1093 #> 2186 81.2 1 1840 1840-01-01 00:00:00 bone 1093 #> 2187 87.7 2 1840 1840-01-31 12:00:00 blood 1094 #> 2188 87.7 2 1840 1840-01-31 12:00:00 bone 1094 #> 2189 55.5 3 1840 1840-03-02 00:00:01 blood 1095 #> 2190 55.5 3 1840 1840-03-02 00:00:01 bone 1095 #> 2191 65.9 4 1840 1840-04-01 12:00:00 blood 1096 #> 2192 65.9 4 1840 1840-04-01 12:00:00 bone 1096 #> 2193 69.2 5 1840 1840-05-02 00:00:00 blood 1097 #> 2194 69.2 5 1840 1840-05-02 00:00:00 bone 1097 #> 2195 48.5 6 1840 1840-06-01 12:00:01 blood 1098 #> 2196 48.5 6 1840 1840-06-01 12:00:01 bone 1098 #> 2197 60.7 7 1840 1840-07-02 00:00:00 blood 1099 #> 2198 60.7 7 1840 1840-07-02 00:00:00 bone 1099 #> 2199 57.8 8 1840 1840-08-01 12:00:00 blood 1100 #> 2200 57.8 8 1840 1840-08-01 12:00:00 bone 1100 #> 2201 74.0 9 1840 1840-09-01 00:00:01 blood 1101 #> 2202 74.0 9 1840 1840-09-01 00:00:01 bone 1101 #> 2203 49.8 10 1840 1840-10-01 12:00:00 blood 1102 #> 2204 49.8 10 1840 1840-10-01 12:00:00 bone 1102 #> 2205 54.3 11 1840 1840-11-01 00:00:00 blood 1103 #> 2206 54.3 11 1840 1840-11-01 00:00:00 bone 1103 #> 2207 53.7 12 1840 1840-12-01 12:00:01 blood 1104 #> 2208 53.7 12 1840 1840-12-01 12:00:01 bone 1104 #> 2209 24.0 1 1841 1841-01-01 00:00:00 blood 1105 #> 2210 24.0 1 1841 1841-01-01 00:00:00 bone 1105 #> 2211 29.9 2 1841 1841-01-31 10:00:00 blood 1106 #> 2212 29.9 2 1841 1841-01-31 10:00:00 bone 1106 #> 2213 29.7 3 1841 1841-03-02 20:00:01 blood 1107 #> 2214 29.7 3 1841 1841-03-02 20:00:01 bone 1107 #> 2215 42.6 4 1841 1841-04-02 06:00:00 blood 1108 #> 2216 42.6 4 1841 1841-04-02 06:00:00 bone 1108 #> 2217 67.4 5 1841 1841-05-02 16:00:00 blood 1109 #> 2218 67.4 5 1841 1841-05-02 16:00:00 bone 1109 #> 2219 55.7 6 1841 1841-06-02 02:00:01 blood 1110 #> 2220 55.7 6 1841 1841-06-02 02:00:01 bone 1110 #> 2221 30.8 7 1841 1841-07-02 12:00:00 blood 1111 #> 2222 30.8 7 1841 1841-07-02 12:00:00 bone 1111 #> 2223 39.3 8 1841 1841-08-01 22:00:00 blood 1112 #> 2224 39.3 8 1841 1841-08-01 22:00:00 bone 1112 #> 2225 35.1 9 1841 1841-09-01 08:00:01 blood 1113 #> 2226 35.1 9 1841 1841-09-01 08:00:01 bone 1113 #> 2227 28.5 10 1841 1841-10-01 18:00:00 blood 1114 #> 2228 28.5 10 1841 1841-10-01 18:00:00 bone 1114 #> 2229 19.8 11 1841 1841-11-01 04:00:00 blood 1115 #> 2230 19.8 11 1841 1841-11-01 04:00:00 bone 1115 #> 2231 38.8 12 1841 1841-12-01 14:00:01 blood 1116 #> 2232 38.8 12 1841 1841-12-01 14:00:01 bone 1116 #> 2233 20.4 1 1842 1842-01-01 00:00:00 blood 1117 #> 2234 20.4 1 1842 1842-01-01 00:00:00 bone 1117 #> 2235 22.1 2 1842 1842-01-31 10:00:00 blood 1118 #> 2236 22.1 2 1842 1842-01-31 10:00:00 bone 1118 #> 2237 21.7 3 1842 1842-03-02 20:00:01 blood 1119 #> 2238 21.7 3 1842 1842-03-02 20:00:01 bone 1119 #> 2239 26.9 4 1842 1842-04-02 06:00:00 blood 1120 #> 2240 26.9 4 1842 1842-04-02 06:00:00 bone 1120 #> 2241 24.9 5 1842 1842-05-02 16:00:00 blood 1121 #> 2242 24.9 5 1842 1842-05-02 16:00:00 bone 1121 #> 2243 20.5 6 1842 1842-06-02 02:00:01 blood 1122 #> 2244 20.5 6 1842 1842-06-02 02:00:01 bone 1122 #> 2245 12.6 7 1842 1842-07-02 12:00:00 blood 1123 #> 2246 12.6 7 1842 1842-07-02 12:00:00 bone 1123 #> 2247 26.5 8 1842 1842-08-01 22:00:00 blood 1124 #> 2248 26.5 8 1842 1842-08-01 22:00:00 bone 1124 #> 2249 18.5 9 1842 1842-09-01 08:00:01 blood 1125 #> 2250 18.5 9 1842 1842-09-01 08:00:01 bone 1125 #> 2251 38.1 10 1842 1842-10-01 18:00:00 blood 1126 #> 2252 38.1 10 1842 1842-10-01 18:00:00 bone 1126 #> 2253 40.5 11 1842 1842-11-01 04:00:00 blood 1127 #> 2254 40.5 11 1842 1842-11-01 04:00:00 bone 1127 #> 2255 17.6 12 1842 1842-12-01 14:00:01 blood 1128 #> 2256 17.6 12 1842 1842-12-01 14:00:01 bone 1128 #> 2257 13.3 1 1843 1843-01-01 00:00:00 blood 1129 #> 2258 13.3 1 1843 1843-01-01 00:00:00 bone 1129 #> 2259 3.5 2 1843 1843-01-31 10:00:00 blood 1130 #> 2260 3.5 2 1843 1843-01-31 10:00:00 bone 1130 #> 2261 8.3 3 1843 1843-03-02 20:00:01 blood 1131 #> 2262 8.3 3 1843 1843-03-02 20:00:01 bone 1131 #> 2263 8.8 4 1843 1843-04-02 06:00:00 blood 1132 #> 2264 8.8 4 1843 1843-04-02 06:00:00 bone 1132 #> 2265 21.1 5 1843 1843-05-02 16:00:00 blood 1133 #> 2266 21.1 5 1843 1843-05-02 16:00:00 bone 1133 #> 2267 10.5 6 1843 1843-06-02 02:00:01 blood 1134 #> 2268 10.5 6 1843 1843-06-02 02:00:01 bone 1134 #> 2269 9.5 7 1843 1843-07-02 12:00:00 blood 1135 #> 2270 9.5 7 1843 1843-07-02 12:00:00 bone 1135 #> 2271 11.8 8 1843 1843-08-01 22:00:00 blood 1136 #> 2272 11.8 8 1843 1843-08-01 22:00:00 bone 1136 #> 2273 4.2 9 1843 1843-09-01 08:00:01 blood 1137 #> 2274 4.2 9 1843 1843-09-01 08:00:01 bone 1137 #> 2275 5.3 10 1843 1843-10-01 18:00:00 blood 1138 #> 2276 5.3 10 1843 1843-10-01 18:00:00 bone 1138 #> 2277 19.1 11 1843 1843-11-01 04:00:00 blood 1139 #> 2278 19.1 11 1843 1843-11-01 04:00:00 bone 1139 #> 2279 12.7 12 1843 1843-12-01 14:00:01 blood 1140 #> 2280 12.7 12 1843 1843-12-01 14:00:01 bone 1140 #> 2281 9.4 1 1844 1844-01-01 00:00:00 blood 1141 #> 2282 9.4 1 1844 1844-01-01 00:00:00 bone 1141 #> 2283 14.7 2 1844 1844-01-31 12:00:00 blood 1142 #> 2284 14.7 2 1844 1844-01-31 12:00:00 bone 1142 #> 2285 13.6 3 1844 1844-03-02 00:00:01 blood 1143 #> 2286 13.6 3 1844 1844-03-02 00:00:01 bone 1143 #> 2287 20.8 4 1844 1844-04-01 12:00:00 blood 1144 #> 2288 20.8 4 1844 1844-04-01 12:00:00 bone 1144 #> 2289 12.0 5 1844 1844-05-02 00:00:00 blood 1145 #> 2290 12.0 5 1844 1844-05-02 00:00:00 bone 1145 #> 2291 3.7 6 1844 1844-06-01 12:00:01 blood 1146 #> 2292 3.7 6 1844 1844-06-01 12:00:01 bone 1146 #> 2293 21.2 7 1844 1844-07-02 00:00:00 blood 1147 #> 2294 21.2 7 1844 1844-07-02 00:00:00 bone 1147 #> 2295 23.9 8 1844 1844-08-01 12:00:00 blood 1148 #> 2296 23.9 8 1844 1844-08-01 12:00:00 bone 1148 #> 2297 6.9 9 1844 1844-09-01 00:00:01 blood 1149 #> 2298 6.9 9 1844 1844-09-01 00:00:01 bone 1149 #> 2299 21.5 10 1844 1844-10-01 12:00:00 blood 1150 #> 2300 21.5 10 1844 1844-10-01 12:00:00 bone 1150 #> 2301 10.7 11 1844 1844-11-01 00:00:00 blood 1151 #> 2302 10.7 11 1844 1844-11-01 00:00:00 bone 1151 #> 2303 21.6 12 1844 1844-12-01 12:00:01 blood 1152 #> 2304 21.6 12 1844 1844-12-01 12:00:01 bone 1152 #> 2305 25.7 1 1845 1845-01-01 00:00:00 blood 1153 #> 2306 25.7 1 1845 1845-01-01 00:00:00 bone 1153 #> 2307 43.6 2 1845 1845-01-31 10:00:00 blood 1154 #> 2308 43.6 2 1845 1845-01-31 10:00:00 bone 1154 #> 2309 43.3 3 1845 1845-03-02 20:00:01 blood 1155 #> 2310 43.3 3 1845 1845-03-02 20:00:01 bone 1155 #> 2311 56.9 4 1845 1845-04-02 06:00:00 blood 1156 #> 2312 56.9 4 1845 1845-04-02 06:00:00 bone 1156 #> 2313 47.8 5 1845 1845-05-02 16:00:00 blood 1157 #> 2314 47.8 5 1845 1845-05-02 16:00:00 bone 1157 #> 2315 31.1 6 1845 1845-06-02 02:00:01 blood 1158 #> 2316 31.1 6 1845 1845-06-02 02:00:01 bone 1158 #> 2317 30.6 7 1845 1845-07-02 12:00:00 blood 1159 #> 2318 30.6 7 1845 1845-07-02 12:00:00 bone 1159 #> 2319 32.3 8 1845 1845-08-01 22:00:00 blood 1160 #> 2320 32.3 8 1845 1845-08-01 22:00:00 bone 1160 #> 2321 29.6 9 1845 1845-09-01 08:00:01 blood 1161 #> 2322 29.6 9 1845 1845-09-01 08:00:01 bone 1161 #> 2323 40.7 10 1845 1845-10-01 18:00:00 blood 1162 #> 2324 40.7 10 1845 1845-10-01 18:00:00 bone 1162 #> 2325 39.4 11 1845 1845-11-01 04:00:00 blood 1163 #> 2326 39.4 11 1845 1845-11-01 04:00:00 bone 1163 #> 2327 59.7 12 1845 1845-12-01 14:00:01 blood 1164 #> 2328 59.7 12 1845 1845-12-01 14:00:01 bone 1164 #> 2329 38.7 1 1846 1846-01-01 00:00:00 blood 1165 #> 2330 38.7 1 1846 1846-01-01 00:00:00 bone 1165 #> 2331 51.0 2 1846 1846-01-31 10:00:00 blood 1166 #> 2332 51.0 2 1846 1846-01-31 10:00:00 bone 1166 #> 2333 63.9 3 1846 1846-03-02 20:00:01 blood 1167 #> 2334 63.9 3 1846 1846-03-02 20:00:01 bone 1167 #> 2335 69.2 4 1846 1846-04-02 06:00:00 blood 1168 #> 2336 69.2 4 1846 1846-04-02 06:00:00 bone 1168 #> 2337 59.9 5 1846 1846-05-02 16:00:00 blood 1169 #> 2338 59.9 5 1846 1846-05-02 16:00:00 bone 1169 #> 2339 65.1 6 1846 1846-06-02 02:00:01 blood 1170 #> 2340 65.1 6 1846 1846-06-02 02:00:01 bone 1170 #> 2341 46.5 7 1846 1846-07-02 12:00:00 blood 1171 #> 2342 46.5 7 1846 1846-07-02 12:00:00 bone 1171 #> 2343 54.8 8 1846 1846-08-01 22:00:00 blood 1172 #> 2344 54.8 8 1846 1846-08-01 22:00:00 bone 1172 #> 2345 107.1 9 1846 1846-09-01 08:00:01 blood 1173 #> 2346 107.1 9 1846 1846-09-01 08:00:01 bone 1173 #> 2347 55.9 10 1846 1846-10-01 18:00:00 blood 1174 #> 2348 55.9 10 1846 1846-10-01 18:00:00 bone 1174 #> 2349 60.4 11 1846 1846-11-01 04:00:00 blood 1175 #> 2350 60.4 11 1846 1846-11-01 04:00:00 bone 1175 #> 2351 65.5 12 1846 1846-12-01 14:00:01 blood 1176 #> 2352 65.5 12 1846 1846-12-01 14:00:01 bone 1176 #> 2353 62.6 1 1847 1847-01-01 00:00:00 blood 1177 #> 2354 62.6 1 1847 1847-01-01 00:00:00 bone 1177 #> 2355 44.9 2 1847 1847-01-31 10:00:00 blood 1178 #> 2356 44.9 2 1847 1847-01-31 10:00:00 bone 1178 #> 2357 85.7 3 1847 1847-03-02 20:00:01 blood 1179 #> 2358 85.7 3 1847 1847-03-02 20:00:01 bone 1179 #> 2359 44.7 4 1847 1847-04-02 06:00:00 blood 1180 #> 2360 44.7 4 1847 1847-04-02 06:00:00 bone 1180 #> 2361 75.4 5 1847 1847-05-02 16:00:00 blood 1181 #> 2362 75.4 5 1847 1847-05-02 16:00:00 bone 1181 #> 2363 85.3 6 1847 1847-06-02 02:00:01 blood 1182 #> 2364 85.3 6 1847 1847-06-02 02:00:01 bone 1182 #> 2365 52.2 7 1847 1847-07-02 12:00:00 blood 1183 #> 2366 52.2 7 1847 1847-07-02 12:00:00 bone 1183 #> 2367 140.6 8 1847 1847-08-01 22:00:00 blood 1184 #> 2368 140.6 8 1847 1847-08-01 22:00:00 bone 1184 #> 2369 161.2 9 1847 1847-09-01 08:00:01 blood 1185 #> 2370 161.2 9 1847 1847-09-01 08:00:01 bone 1185 #> 2371 180.4 10 1847 1847-10-01 18:00:00 blood 1186 #> 2372 180.4 10 1847 1847-10-01 18:00:00 bone 1186 #> 2373 138.9 11 1847 1847-11-01 04:00:00 blood 1187 #> 2374 138.9 11 1847 1847-11-01 04:00:00 bone 1187 #> 2375 109.6 12 1847 1847-12-01 14:00:01 blood 1188 #> 2376 109.6 12 1847 1847-12-01 14:00:01 bone 1188 #> 2377 159.1 1 1848 1848-01-01 00:00:00 blood 1189 #> 2378 159.1 1 1848 1848-01-01 00:00:00 bone 1189 #> 2379 111.8 2 1848 1848-01-31 12:00:00 blood 1190 #> 2380 111.8 2 1848 1848-01-31 12:00:00 bone 1190 #> 2381 108.9 3 1848 1848-03-02 00:00:01 blood 1191 #> 2382 108.9 3 1848 1848-03-02 00:00:01 bone 1191 #> 2383 107.1 4 1848 1848-04-01 12:00:00 blood 1192 #> 2384 107.1 4 1848 1848-04-01 12:00:00 bone 1192 #> 2385 102.2 5 1848 1848-05-02 00:00:00 blood 1193 #> 2386 102.2 5 1848 1848-05-02 00:00:00 bone 1193 #> 2387 123.8 6 1848 1848-06-01 12:00:01 blood 1194 #> 2388 123.8 6 1848 1848-06-01 12:00:01 bone 1194 #> 2389 139.2 7 1848 1848-07-02 00:00:00 blood 1195 #> 2390 139.2 7 1848 1848-07-02 00:00:00 bone 1195 #> 2391 132.5 8 1848 1848-08-01 12:00:00 blood 1196 #> 2392 132.5 8 1848 1848-08-01 12:00:00 bone 1196 #> 2393 100.3 9 1848 1848-09-01 00:00:01 blood 1197 #> 2394 100.3 9 1848 1848-09-01 00:00:01 bone 1197 #> 2395 132.4 10 1848 1848-10-01 12:00:00 blood 1198 #> 2396 132.4 10 1848 1848-10-01 12:00:00 bone 1198 #> 2397 114.6 11 1848 1848-11-01 00:00:00 blood 1199 #> 2398 114.6 11 1848 1848-11-01 00:00:00 bone 1199 #> 2399 159.9 12 1848 1848-12-01 12:00:01 blood 1200 #> 2400 159.9 12 1848 1848-12-01 12:00:01 bone 1200 #> 2401 156.7 1 1849 1849-01-01 00:00:00 blood 1201 #> 2402 156.7 1 1849 1849-01-01 00:00:00 bone 1201 #> 2403 131.7 2 1849 1849-01-31 10:00:00 blood 1202 #> 2404 131.7 2 1849 1849-01-31 10:00:00 bone 1202 #> 2405 96.5 3 1849 1849-03-02 20:00:01 blood 1203 #> 2406 96.5 3 1849 1849-03-02 20:00:01 bone 1203 #> 2407 102.5 4 1849 1849-04-02 06:00:00 blood 1204 #> 2408 102.5 4 1849 1849-04-02 06:00:00 bone 1204 #> 2409 80.6 5 1849 1849-05-02 16:00:00 blood 1205 #> 2410 80.6 5 1849 1849-05-02 16:00:00 bone 1205 #> 2411 81.2 6 1849 1849-06-02 02:00:01 blood 1206 #> 2412 81.2 6 1849 1849-06-02 02:00:01 bone 1206 #> 2413 78.0 7 1849 1849-07-02 12:00:00 blood 1207 #> 2414 78.0 7 1849 1849-07-02 12:00:00 bone 1207 #> 2415 61.3 8 1849 1849-08-01 22:00:00 blood 1208 #> 2416 61.3 8 1849 1849-08-01 22:00:00 bone 1208 #> 2417 93.7 9 1849 1849-09-01 08:00:01 blood 1209 #> 2418 93.7 9 1849 1849-09-01 08:00:01 bone 1209 #> 2419 71.5 10 1849 1849-10-01 18:00:00 blood 1210 #> 2420 71.5 10 1849 1849-10-01 18:00:00 bone 1210 #> 2421 99.7 11 1849 1849-11-01 04:00:00 blood 1211 #> 2422 99.7 11 1849 1849-11-01 04:00:00 bone 1211 #> 2423 97.0 12 1849 1849-12-01 14:00:01 blood 1212 #> 2424 97.0 12 1849 1849-12-01 14:00:01 bone 1212 #> 2425 78.0 1 1850 1850-01-01 00:00:00 blood 1213 #> 2426 78.0 1 1850 1850-01-01 00:00:00 bone 1213 #> 2427 89.4 2 1850 1850-01-31 10:00:00 blood 1214 #> 2428 89.4 2 1850 1850-01-31 10:00:00 bone 1214 #> 2429 82.6 3 1850 1850-03-02 20:00:01 blood 1215 #> 2430 82.6 3 1850 1850-03-02 20:00:01 bone 1215 #> 2431 44.1 4 1850 1850-04-02 06:00:00 blood 1216 #> 2432 44.1 4 1850 1850-04-02 06:00:00 bone 1216 #> 2433 61.6 5 1850 1850-05-02 16:00:00 blood 1217 #> 2434 61.6 5 1850 1850-05-02 16:00:00 bone 1217 #> 2435 70.0 6 1850 1850-06-02 02:00:01 blood 1218 #> 2436 70.0 6 1850 1850-06-02 02:00:01 bone 1218 #> 2437 39.1 7 1850 1850-07-02 12:00:00 blood 1219 #> 2438 39.1 7 1850 1850-07-02 12:00:00 bone 1219 #> 2439 61.6 8 1850 1850-08-01 22:00:00 blood 1220 #> 2440 61.6 8 1850 1850-08-01 22:00:00 bone 1220 #> 2441 86.2 9 1850 1850-09-01 08:00:01 blood 1221 #> 2442 86.2 9 1850 1850-09-01 08:00:01 bone 1221 #> 2443 71.0 10 1850 1850-10-01 18:00:00 blood 1222 #> 2444 71.0 10 1850 1850-10-01 18:00:00 bone 1222 #> 2445 54.8 11 1850 1850-11-01 04:00:00 blood 1223 #> 2446 54.8 11 1850 1850-11-01 04:00:00 bone 1223 #> 2447 60.0 12 1850 1850-12-01 14:00:01 blood 1224 #> 2448 60.0 12 1850 1850-12-01 14:00:01 bone 1224 #> 2449 75.5 1 1851 1851-01-01 00:00:00 blood 1225 #> 2450 75.5 1 1851 1851-01-01 00:00:00 bone 1225 #> 2451 105.4 2 1851 1851-01-31 10:00:00 blood 1226 #> 2452 105.4 2 1851 1851-01-31 10:00:00 bone 1226 #> 2453 64.6 3 1851 1851-03-02 20:00:01 blood 1227 #> 2454 64.6 3 1851 1851-03-02 20:00:01 bone 1227 #> 2455 56.5 4 1851 1851-04-02 06:00:00 blood 1228 #> 2456 56.5 4 1851 1851-04-02 06:00:00 bone 1228 #> 2457 62.6 5 1851 1851-05-02 16:00:00 blood 1229 #> 2458 62.6 5 1851 1851-05-02 16:00:00 bone 1229 #> 2459 63.2 6 1851 1851-06-02 02:00:01 blood 1230 #> 2460 63.2 6 1851 1851-06-02 02:00:01 bone 1230 #> 2461 36.1 7 1851 1851-07-02 12:00:00 blood 1231 #> 2462 36.1 7 1851 1851-07-02 12:00:00 bone 1231 #> 2463 57.4 8 1851 1851-08-01 22:00:00 blood 1232 #> 2464 57.4 8 1851 1851-08-01 22:00:00 bone 1232 #> 2465 67.9 9 1851 1851-09-01 08:00:01 blood 1233 #> 2466 67.9 9 1851 1851-09-01 08:00:01 bone 1233 #> 2467 62.5 10 1851 1851-10-01 18:00:00 blood 1234 #> 2468 62.5 10 1851 1851-10-01 18:00:00 bone 1234 #> 2469 50.9 11 1851 1851-11-01 04:00:00 blood 1235 #> 2470 50.9 11 1851 1851-11-01 04:00:00 bone 1235 #> 2471 71.4 12 1851 1851-12-01 14:00:01 blood 1236 #> 2472 71.4 12 1851 1851-12-01 14:00:01 bone 1236 #> 2473 68.4 1 1852 1852-01-01 00:00:00 blood 1237 #> 2474 68.4 1 1852 1852-01-01 00:00:00 bone 1237 #> 2475 67.5 2 1852 1852-01-31 12:00:00 blood 1238 #> 2476 67.5 2 1852 1852-01-31 12:00:00 bone 1238 #> 2477 61.2 3 1852 1852-03-02 00:00:01 blood 1239 #> 2478 61.2 3 1852 1852-03-02 00:00:01 bone 1239 #> 2479 65.4 4 1852 1852-04-01 12:00:00 blood 1240 #> 2480 65.4 4 1852 1852-04-01 12:00:00 bone 1240 #> 2481 54.9 5 1852 1852-05-02 00:00:00 blood 1241 #> 2482 54.9 5 1852 1852-05-02 00:00:00 bone 1241 #> 2483 46.9 6 1852 1852-06-01 12:00:01 blood 1242 #> 2484 46.9 6 1852 1852-06-01 12:00:01 bone 1242 #> 2485 42.0 7 1852 1852-07-02 00:00:00 blood 1243 #> 2486 42.0 7 1852 1852-07-02 00:00:00 bone 1243 #> 2487 39.7 8 1852 1852-08-01 12:00:00 blood 1244 #> 2488 39.7 8 1852 1852-08-01 12:00:00 bone 1244 #> 2489 37.5 9 1852 1852-09-01 00:00:01 blood 1245 #> 2490 37.5 9 1852 1852-09-01 00:00:01 bone 1245 #> 2491 67.3 10 1852 1852-10-01 12:00:00 blood 1246 #> 2492 67.3 10 1852 1852-10-01 12:00:00 bone 1246 #> 2493 54.3 11 1852 1852-11-01 00:00:00 blood 1247 #> 2494 54.3 11 1852 1852-11-01 00:00:00 bone 1247 #> 2495 45.4 12 1852 1852-12-01 12:00:01 blood 1248 #> 2496 45.4 12 1852 1852-12-01 12:00:01 bone 1248 #> 2497 41.1 1 1853 1853-01-01 00:00:00 blood 1249 #> 2498 41.1 1 1853 1853-01-01 00:00:00 bone 1249 #> 2499 42.9 2 1853 1853-01-31 10:00:00 blood 1250 #> 2500 42.9 2 1853 1853-01-31 10:00:00 bone 1250 #> 2501 37.7 3 1853 1853-03-02 20:00:01 blood 1251 #> 2502 37.7 3 1853 1853-03-02 20:00:01 bone 1251 #> 2503 47.6 4 1853 1853-04-02 06:00:00 blood 1252 #> 2504 47.6 4 1853 1853-04-02 06:00:00 bone 1252 #> 2505 34.7 5 1853 1853-05-02 16:00:00 blood 1253 #> 2506 34.7 5 1853 1853-05-02 16:00:00 bone 1253 #> 2507 40.0 6 1853 1853-06-02 02:00:01 blood 1254 #> 2508 40.0 6 1853 1853-06-02 02:00:01 bone 1254 #> 2509 45.9 7 1853 1853-07-02 12:00:00 blood 1255 #> 2510 45.9 7 1853 1853-07-02 12:00:00 bone 1255 #> 2511 50.4 8 1853 1853-08-01 22:00:00 blood 1256 #> 2512 50.4 8 1853 1853-08-01 22:00:00 bone 1256 #> 2513 33.5 9 1853 1853-09-01 08:00:01 blood 1257 #> 2514 33.5 9 1853 1853-09-01 08:00:01 bone 1257 #> 2515 42.3 10 1853 1853-10-01 18:00:00 blood 1258 #> 2516 42.3 10 1853 1853-10-01 18:00:00 bone 1258 #> 2517 28.8 11 1853 1853-11-01 04:00:00 blood 1259 #> 2518 28.8 11 1853 1853-11-01 04:00:00 bone 1259 #> 2519 23.4 12 1853 1853-12-01 14:00:01 blood 1260 #> 2520 23.4 12 1853 1853-12-01 14:00:01 bone 1260 #> 2521 15.4 1 1854 1854-01-01 00:00:00 blood 1261 #> 2522 15.4 1 1854 1854-01-01 00:00:00 bone 1261 #> 2523 20.0 2 1854 1854-01-31 10:00:00 blood 1262 #> 2524 20.0 2 1854 1854-01-31 10:00:00 bone 1262 #> 2525 20.7 3 1854 1854-03-02 20:00:01 blood 1263 #> 2526 20.7 3 1854 1854-03-02 20:00:01 bone 1263 #> 2527 26.4 4 1854 1854-04-02 06:00:00 blood 1264 #> 2528 26.4 4 1854 1854-04-02 06:00:00 bone 1264 #> 2529 24.0 5 1854 1854-05-02 16:00:00 blood 1265 #> 2530 24.0 5 1854 1854-05-02 16:00:00 bone 1265 #> 2531 21.1 6 1854 1854-06-02 02:00:01 blood 1266 #> 2532 21.1 6 1854 1854-06-02 02:00:01 bone 1266 #> 2533 18.7 7 1854 1854-07-02 12:00:00 blood 1267 #> 2534 18.7 7 1854 1854-07-02 12:00:00 bone 1267 #> 2535 15.8 8 1854 1854-08-01 22:00:00 blood 1268 #> 2536 15.8 8 1854 1854-08-01 22:00:00 bone 1268 #> 2537 22.4 9 1854 1854-09-01 08:00:01 blood 1269 #> 2538 22.4 9 1854 1854-09-01 08:00:01 bone 1269 #> 2539 12.7 10 1854 1854-10-01 18:00:00 blood 1270 #> 2540 12.7 10 1854 1854-10-01 18:00:00 bone 1270 #> 2541 28.2 11 1854 1854-11-01 04:00:00 blood 1271 #> 2542 28.2 11 1854 1854-11-01 04:00:00 bone 1271 #> 2543 21.4 12 1854 1854-12-01 14:00:01 blood 1272 #> 2544 21.4 12 1854 1854-12-01 14:00:01 bone 1272 #> 2545 12.3 1 1855 1855-01-01 00:00:00 blood 1273 #> 2546 12.3 1 1855 1855-01-01 00:00:00 bone 1273 #> 2547 11.4 2 1855 1855-01-31 10:00:00 blood 1274 #> 2548 11.4 2 1855 1855-01-31 10:00:00 bone 1274 #> 2549 17.4 3 1855 1855-03-02 20:00:01 blood 1275 #> 2550 17.4 3 1855 1855-03-02 20:00:01 bone 1275 #> 2551 4.4 4 1855 1855-04-02 06:00:00 blood 1276 #> 2552 4.4 4 1855 1855-04-02 06:00:00 bone 1276 #> 2553 9.1 5 1855 1855-05-02 16:00:00 blood 1277 #> 2554 9.1 5 1855 1855-05-02 16:00:00 bone 1277 #> 2555 5.3 6 1855 1855-06-02 02:00:01 blood 1278 #> 2556 5.3 6 1855 1855-06-02 02:00:01 bone 1278 #> 2557 0.4 7 1855 1855-07-02 12:00:00 blood 1279 #> 2558 0.4 7 1855 1855-07-02 12:00:00 bone 1279 #> 2559 3.1 8 1855 1855-08-01 22:00:00 blood 1280 #> 2560 3.1 8 1855 1855-08-01 22:00:00 bone 1280 #> 2561 0.0 9 1855 1855-09-01 08:00:01 blood 1281 #> 2562 0.0 9 1855 1855-09-01 08:00:01 bone 1281 #> 2563 9.7 10 1855 1855-10-01 18:00:00 blood 1282 #> 2564 9.7 10 1855 1855-10-01 18:00:00 bone 1282 #> 2565 4.3 11 1855 1855-11-01 04:00:00 blood 1283 #> 2566 4.3 11 1855 1855-11-01 04:00:00 bone 1283 #> 2567 3.1 12 1855 1855-12-01 14:00:01 blood 1284 #> 2568 3.1 12 1855 1855-12-01 14:00:01 bone 1284 #> 2569 0.5 1 1856 1856-01-01 00:00:00 blood 1285 #> 2570 0.5 1 1856 1856-01-01 00:00:00 bone 1285 #> 2571 4.9 2 1856 1856-01-31 12:00:00 blood 1286 #> 2572 4.9 2 1856 1856-01-31 12:00:00 bone 1286 #> 2573 0.4 3 1856 1856-03-02 00:00:01 blood 1287 #> 2574 0.4 3 1856 1856-03-02 00:00:01 bone 1287 #> 2575 6.5 4 1856 1856-04-01 12:00:00 blood 1288 #> 2576 6.5 4 1856 1856-04-01 12:00:00 bone 1288 #> 2577 0.0 5 1856 1856-05-02 00:00:00 blood 1289 #> 2578 0.0 5 1856 1856-05-02 00:00:00 bone 1289 #> 2579 5.0 6 1856 1856-06-01 12:00:01 blood 1290 #> 2580 5.0 6 1856 1856-06-01 12:00:01 bone 1290 #> 2581 4.6 7 1856 1856-07-02 00:00:00 blood 1291 #> 2582 4.6 7 1856 1856-07-02 00:00:00 bone 1291 #> 2583 5.9 8 1856 1856-08-01 12:00:00 blood 1292 #> 2584 5.9 8 1856 1856-08-01 12:00:00 bone 1292 #> 2585 4.4 9 1856 1856-09-01 00:00:01 blood 1293 #> 2586 4.4 9 1856 1856-09-01 00:00:01 bone 1293 #> 2587 4.5 10 1856 1856-10-01 12:00:00 blood 1294 #> 2588 4.5 10 1856 1856-10-01 12:00:00 bone 1294 #> 2589 7.7 11 1856 1856-11-01 00:00:00 blood 1295 #> 2590 7.7 11 1856 1856-11-01 00:00:00 bone 1295 #> 2591 7.2 12 1856 1856-12-01 12:00:01 blood 1296 #> 2592 7.2 12 1856 1856-12-01 12:00:01 bone 1296 #> 2593 13.7 1 1857 1857-01-01 00:00:00 blood 1297 #> 2594 13.7 1 1857 1857-01-01 00:00:00 bone 1297 #> 2595 7.4 2 1857 1857-01-31 10:00:00 blood 1298 #> 2596 7.4 2 1857 1857-01-31 10:00:00 bone 1298 #> 2597 5.2 3 1857 1857-03-02 20:00:01 blood 1299 #> 2598 5.2 3 1857 1857-03-02 20:00:01 bone 1299 #> 2599 11.1 4 1857 1857-04-02 06:00:00 blood 1300 #> 2600 11.1 4 1857 1857-04-02 06:00:00 bone 1300 #> 2601 29.2 5 1857 1857-05-02 16:00:00 blood 1301 #> 2602 29.2 5 1857 1857-05-02 16:00:00 bone 1301 #> 2603 16.0 6 1857 1857-06-02 02:00:01 blood 1302 #> 2604 16.0 6 1857 1857-06-02 02:00:01 bone 1302 #> 2605 22.2 7 1857 1857-07-02 12:00:00 blood 1303 #> 2606 22.2 7 1857 1857-07-02 12:00:00 bone 1303 #> 2607 16.9 8 1857 1857-08-01 22:00:00 blood 1304 #> 2608 16.9 8 1857 1857-08-01 22:00:00 bone 1304 #> 2609 42.4 9 1857 1857-09-01 08:00:01 blood 1305 #> 2610 42.4 9 1857 1857-09-01 08:00:01 bone 1305 #> 2611 40.6 10 1857 1857-10-01 18:00:00 blood 1306 #> 2612 40.6 10 1857 1857-10-01 18:00:00 bone 1306 #> 2613 31.4 11 1857 1857-11-01 04:00:00 blood 1307 #> 2614 31.4 11 1857 1857-11-01 04:00:00 bone 1307 #> 2615 37.2 12 1857 1857-12-01 14:00:01 blood 1308 #> 2616 37.2 12 1857 1857-12-01 14:00:01 bone 1308 #> 2617 39.0 1 1858 1858-01-01 00:00:00 blood 1309 #> 2618 39.0 1 1858 1858-01-01 00:00:00 bone 1309 #> 2619 34.9 2 1858 1858-01-31 10:00:00 blood 1310 #> 2620 34.9 2 1858 1858-01-31 10:00:00 bone 1310 #> 2621 57.5 3 1858 1858-03-02 20:00:01 blood 1311 #> 2622 57.5 3 1858 1858-03-02 20:00:01 bone 1311 #> 2623 38.3 4 1858 1858-04-02 06:00:00 blood 1312 #> 2624 38.3 4 1858 1858-04-02 06:00:00 bone 1312 #> 2625 41.4 5 1858 1858-05-02 16:00:00 blood 1313 #> 2626 41.4 5 1858 1858-05-02 16:00:00 bone 1313 #> 2627 44.5 6 1858 1858-06-02 02:00:01 blood 1314 #> 2628 44.5 6 1858 1858-06-02 02:00:01 bone 1314 #> 2629 56.7 7 1858 1858-07-02 12:00:00 blood 1315 #> 2630 56.7 7 1858 1858-07-02 12:00:00 bone 1315 #> 2631 55.3 8 1858 1858-08-01 22:00:00 blood 1316 #> 2632 55.3 8 1858 1858-08-01 22:00:00 bone 1316 #> 2633 80.1 9 1858 1858-09-01 08:00:01 blood 1317 #> 2634 80.1 9 1858 1858-09-01 08:00:01 bone 1317 #> 2635 91.2 10 1858 1858-10-01 18:00:00 blood 1318 #> 2636 91.2 10 1858 1858-10-01 18:00:00 bone 1318 #> 2637 51.9 11 1858 1858-11-01 04:00:00 blood 1319 #> 2638 51.9 11 1858 1858-11-01 04:00:00 bone 1319 #> 2639 66.9 12 1858 1858-12-01 14:00:01 blood 1320 #> 2640 66.9 12 1858 1858-12-01 14:00:01 bone 1320 #> 2641 83.7 1 1859 1859-01-01 00:00:00 blood 1321 #> 2642 83.7 1 1859 1859-01-01 00:00:00 bone 1321 #> 2643 87.6 2 1859 1859-01-31 10:00:00 blood 1322 #> 2644 87.6 2 1859 1859-01-31 10:00:00 bone 1322 #> 2645 90.3 3 1859 1859-03-02 20:00:01 blood 1323 #> 2646 90.3 3 1859 1859-03-02 20:00:01 bone 1323 #> 2647 85.7 4 1859 1859-04-02 06:00:00 blood 1324 #> 2648 85.7 4 1859 1859-04-02 06:00:00 bone 1324 #> 2649 91.0 5 1859 1859-05-02 16:00:00 blood 1325 #> 2650 91.0 5 1859 1859-05-02 16:00:00 bone 1325 #> 2651 87.1 6 1859 1859-06-02 02:00:01 blood 1326 #> 2652 87.1 6 1859 1859-06-02 02:00:01 bone 1326 #> 2653 95.2 7 1859 1859-07-02 12:00:00 blood 1327 #> 2654 95.2 7 1859 1859-07-02 12:00:00 bone 1327 #> 2655 106.8 8 1859 1859-08-01 22:00:00 blood 1328 #> 2656 106.8 8 1859 1859-08-01 22:00:00 bone 1328 #> 2657 105.8 9 1859 1859-09-01 08:00:01 blood 1329 #> 2658 105.8 9 1859 1859-09-01 08:00:01 bone 1329 #> 2659 114.6 10 1859 1859-10-01 18:00:00 blood 1330 #> 2660 114.6 10 1859 1859-10-01 18:00:00 bone 1330 #> 2661 97.2 11 1859 1859-11-01 04:00:00 blood 1331 #> 2662 97.2 11 1859 1859-11-01 04:00:00 bone 1331 #> 2663 81.0 12 1859 1859-12-01 14:00:01 blood 1332 #> 2664 81.0 12 1859 1859-12-01 14:00:01 bone 1332 #> 2665 81.5 1 1860 1860-01-01 00:00:00 blood 1333 #> 2666 81.5 1 1860 1860-01-01 00:00:00 bone 1333 #> 2667 88.0 2 1860 1860-01-31 12:00:01 blood 1334 #> 2668 88.0 2 1860 1860-01-31 12:00:01 bone 1334 #> 2669 98.9 3 1860 1860-03-02 00:00:01 blood 1335 #> 2670 98.9 3 1860 1860-03-02 00:00:01 bone 1335 #> 2671 71.4 4 1860 1860-04-01 12:00:00 blood 1336 #> 2672 71.4 4 1860 1860-04-01 12:00:00 bone 1336 #> 2673 107.1 5 1860 1860-05-02 00:00:01 blood 1337 #> 2674 107.1 5 1860 1860-05-02 00:00:01 bone 1337 #> 2675 108.6 6 1860 1860-06-01 12:00:01 blood 1338 #> 2676 108.6 6 1860 1860-06-01 12:00:01 bone 1338 #> 2677 116.7 7 1860 1860-07-02 00:00:00 blood 1339 #> 2678 116.7 7 1860 1860-07-02 00:00:00 bone 1339 #> 2679 100.3 8 1860 1860-08-01 12:00:01 blood 1340 #> 2680 100.3 8 1860 1860-08-01 12:00:01 bone 1340 #> 2681 92.2 9 1860 1860-09-01 00:00:01 blood 1341 #> 2682 92.2 9 1860 1860-09-01 00:00:01 bone 1341 #> 2683 90.1 10 1860 1860-10-01 12:00:00 blood 1342 #> 2684 90.1 10 1860 1860-10-01 12:00:00 bone 1342 #> 2685 97.9 11 1860 1860-11-01 00:00:01 blood 1343 #> 2686 97.9 11 1860 1860-11-01 00:00:01 bone 1343 #> 2687 95.6 12 1860 1860-12-01 12:00:01 blood 1344 #> 2688 95.6 12 1860 1860-12-01 12:00:01 bone 1344 #> 2689 62.3 1 1861 1861-01-01 00:00:00 blood 1345 #> 2690 62.3 1 1861 1861-01-01 00:00:00 bone 1345 #> 2691 77.8 2 1861 1861-01-31 10:00:01 blood 1346 #> 2692 77.8 2 1861 1861-01-31 10:00:01 bone 1346 #> 2693 101.0 3 1861 1861-03-02 20:00:01 blood 1347 #> 2694 101.0 3 1861 1861-03-02 20:00:01 bone 1347 #> 2695 98.5 4 1861 1861-04-02 06:00:00 blood 1348 #> 2696 98.5 4 1861 1861-04-02 06:00:00 bone 1348 #> 2697 56.8 5 1861 1861-05-02 16:00:01 blood 1349 #> 2698 56.8 5 1861 1861-05-02 16:00:01 bone 1349 #> 2699 87.8 6 1861 1861-06-02 02:00:01 blood 1350 #> 2700 87.8 6 1861 1861-06-02 02:00:01 bone 1350 #> 2701 78.0 7 1861 1861-07-02 12:00:00 blood 1351 #> 2702 78.0 7 1861 1861-07-02 12:00:00 bone 1351 #> 2703 82.5 8 1861 1861-08-01 22:00:01 blood 1352 #> 2704 82.5 8 1861 1861-08-01 22:00:01 bone 1352 #> 2705 79.9 9 1861 1861-09-01 08:00:01 blood 1353 #> 2706 79.9 9 1861 1861-09-01 08:00:01 bone 1353 #> 2707 67.2 10 1861 1861-10-01 18:00:00 blood 1354 #> 2708 67.2 10 1861 1861-10-01 18:00:00 bone 1354 #> 2709 53.7 11 1861 1861-11-01 04:00:01 blood 1355 #> 2710 53.7 11 1861 1861-11-01 04:00:01 bone 1355 #> 2711 80.5 12 1861 1861-12-01 14:00:01 blood 1356 #> 2712 80.5 12 1861 1861-12-01 14:00:01 bone 1356 #> 2713 63.1 1 1862 1862-01-01 00:00:00 blood 1357 #> 2714 63.1 1 1862 1862-01-01 00:00:00 bone 1357 #> 2715 64.5 2 1862 1862-01-31 10:00:01 blood 1358 #> 2716 64.5 2 1862 1862-01-31 10:00:01 bone 1358 #> 2717 43.6 3 1862 1862-03-02 20:00:01 blood 1359 #> 2718 43.6 3 1862 1862-03-02 20:00:01 bone 1359 #> 2719 53.7 4 1862 1862-04-02 06:00:00 blood 1360 #> 2720 53.7 4 1862 1862-04-02 06:00:00 bone 1360 #> 2721 64.4 5 1862 1862-05-02 16:00:01 blood 1361 #> 2722 64.4 5 1862 1862-05-02 16:00:01 bone 1361 #> 2723 84.0 6 1862 1862-06-02 02:00:01 blood 1362 #> 2724 84.0 6 1862 1862-06-02 02:00:01 bone 1362 #> 2725 73.4 7 1862 1862-07-02 12:00:00 blood 1363 #> 2726 73.4 7 1862 1862-07-02 12:00:00 bone 1363 #> 2727 62.5 8 1862 1862-08-01 22:00:01 blood 1364 #> 2728 62.5 8 1862 1862-08-01 22:00:01 bone 1364 #> 2729 66.6 9 1862 1862-09-01 08:00:01 blood 1365 #> 2730 66.6 9 1862 1862-09-01 08:00:01 bone 1365 #> 2731 42.0 10 1862 1862-10-01 18:00:00 blood 1366 #> 2732 42.0 10 1862 1862-10-01 18:00:00 bone 1366 #> 2733 50.6 11 1862 1862-11-01 04:00:01 blood 1367 #> 2734 50.6 11 1862 1862-11-01 04:00:01 bone 1367 #> 2735 40.9 12 1862 1862-12-01 14:00:01 blood 1368 #> 2736 40.9 12 1862 1862-12-01 14:00:01 bone 1368 #> 2737 48.3 1 1863 1863-01-01 00:00:00 blood 1369 #> 2738 48.3 1 1863 1863-01-01 00:00:00 bone 1369 #> 2739 56.7 2 1863 1863-01-31 10:00:01 blood 1370 #> 2740 56.7 2 1863 1863-01-31 10:00:01 bone 1370 #> 2741 66.4 3 1863 1863-03-02 20:00:01 blood 1371 #> 2742 66.4 3 1863 1863-03-02 20:00:01 bone 1371 #> 2743 40.6 4 1863 1863-04-02 06:00:00 blood 1372 #> 2744 40.6 4 1863 1863-04-02 06:00:00 bone 1372 #> 2745 53.8 5 1863 1863-05-02 16:00:01 blood 1373 #> 2746 53.8 5 1863 1863-05-02 16:00:01 bone 1373 #> 2747 40.8 6 1863 1863-06-02 02:00:01 blood 1374 #> 2748 40.8 6 1863 1863-06-02 02:00:01 bone 1374 #> 2749 32.7 7 1863 1863-07-02 12:00:00 blood 1375 #> 2750 32.7 7 1863 1863-07-02 12:00:00 bone 1375 #> 2751 48.1 8 1863 1863-08-01 22:00:01 blood 1376 #> 2752 48.1 8 1863 1863-08-01 22:00:01 bone 1376 #> 2753 22.0 9 1863 1863-09-01 08:00:01 blood 1377 #> 2754 22.0 9 1863 1863-09-01 08:00:01 bone 1377 #> 2755 39.9 10 1863 1863-10-01 18:00:00 blood 1378 #> 2756 39.9 10 1863 1863-10-01 18:00:00 bone 1378 #> 2757 37.7 11 1863 1863-11-01 04:00:01 blood 1379 #> 2758 37.7 11 1863 1863-11-01 04:00:01 bone 1379 #> 2759 41.2 12 1863 1863-12-01 14:00:01 blood 1380 #> 2760 41.2 12 1863 1863-12-01 14:00:01 bone 1380 #> 2761 57.7 1 1864 1864-01-01 00:00:00 blood 1381 #> 2762 57.7 1 1864 1864-01-01 00:00:00 bone 1381 #> 2763 47.1 2 1864 1864-01-31 12:00:01 blood 1382 #> 2764 47.1 2 1864 1864-01-31 12:00:01 bone 1382 #> 2765 66.3 3 1864 1864-03-02 00:00:01 blood 1383 #> 2766 66.3 3 1864 1864-03-02 00:00:01 bone 1383 #> 2767 35.8 4 1864 1864-04-01 12:00:00 blood 1384 #> 2768 35.8 4 1864 1864-04-01 12:00:00 bone 1384 #> 2769 40.6 5 1864 1864-05-02 00:00:01 blood 1385 #> 2770 40.6 5 1864 1864-05-02 00:00:01 bone 1385 #> 2771 57.8 6 1864 1864-06-01 12:00:01 blood 1386 #> 2772 57.8 6 1864 1864-06-01 12:00:01 bone 1386 #> 2773 54.7 7 1864 1864-07-02 00:00:00 blood 1387 #> 2774 54.7 7 1864 1864-07-02 00:00:00 bone 1387 #> 2775 54.8 8 1864 1864-08-01 12:00:01 blood 1388 #> 2776 54.8 8 1864 1864-08-01 12:00:01 bone 1388 #> 2777 28.5 9 1864 1864-09-01 00:00:01 blood 1389 #> 2778 28.5 9 1864 1864-09-01 00:00:01 bone 1389 #> 2779 33.9 10 1864 1864-10-01 12:00:00 blood 1390 #> 2780 33.9 10 1864 1864-10-01 12:00:00 bone 1390 #> 2781 57.6 11 1864 1864-11-01 00:00:01 blood 1391 #> 2782 57.6 11 1864 1864-11-01 00:00:01 bone 1391 #> 2783 28.6 12 1864 1864-12-01 12:00:01 blood 1392 #> 2784 28.6 12 1864 1864-12-01 12:00:01 bone 1392 #> 2785 48.7 1 1865 1865-01-01 00:00:00 blood 1393 #> 2786 48.7 1 1865 1865-01-01 00:00:00 bone 1393 #> 2787 39.3 2 1865 1865-01-31 10:00:01 blood 1394 #> 2788 39.3 2 1865 1865-01-31 10:00:01 bone 1394 #> 2789 39.5 3 1865 1865-03-02 20:00:01 blood 1395 #> 2790 39.5 3 1865 1865-03-02 20:00:01 bone 1395 #> 2791 29.4 4 1865 1865-04-02 06:00:00 blood 1396 #> 2792 29.4 4 1865 1865-04-02 06:00:00 bone 1396 #> 2793 34.5 5 1865 1865-05-02 16:00:01 blood 1397 #> 2794 34.5 5 1865 1865-05-02 16:00:01 bone 1397 #> 2795 33.6 6 1865 1865-06-02 02:00:01 blood 1398 #> 2796 33.6 6 1865 1865-06-02 02:00:01 bone 1398 #> 2797 26.8 7 1865 1865-07-02 12:00:00 blood 1399 #> 2798 26.8 7 1865 1865-07-02 12:00:00 bone 1399 #> 2799 37.8 8 1865 1865-08-01 22:00:01 blood 1400 #> 2800 37.8 8 1865 1865-08-01 22:00:01 bone 1400 #> 2801 21.6 9 1865 1865-09-01 08:00:01 blood 1401 #> 2802 21.6 9 1865 1865-09-01 08:00:01 bone 1401 #> 2803 17.1 10 1865 1865-10-01 18:00:00 blood 1402 #> 2804 17.1 10 1865 1865-10-01 18:00:00 bone 1402 #> 2805 24.6 11 1865 1865-11-01 04:00:01 blood 1403 #> 2806 24.6 11 1865 1865-11-01 04:00:01 bone 1403 #> 2807 12.8 12 1865 1865-12-01 14:00:01 blood 1404 #> 2808 12.8 12 1865 1865-12-01 14:00:01 bone 1404 #> 2809 31.6 1 1866 1866-01-01 00:00:00 blood 1405 #> 2810 31.6 1 1866 1866-01-01 00:00:00 bone 1405 #> 2811 38.4 2 1866 1866-01-31 10:00:01 blood 1406 #> 2812 38.4 2 1866 1866-01-31 10:00:01 bone 1406 #> 2813 24.6 3 1866 1866-03-02 20:00:01 blood 1407 #> 2814 24.6 3 1866 1866-03-02 20:00:01 bone 1407 #> 2815 17.6 4 1866 1866-04-02 06:00:00 blood 1408 #> 2816 17.6 4 1866 1866-04-02 06:00:00 bone 1408 #> 2817 12.9 5 1866 1866-05-02 16:00:01 blood 1409 #> 2818 12.9 5 1866 1866-05-02 16:00:01 bone 1409 #> 2819 16.5 6 1866 1866-06-02 02:00:01 blood 1410 #> 2820 16.5 6 1866 1866-06-02 02:00:01 bone 1410 #> 2821 9.3 7 1866 1866-07-02 12:00:00 blood 1411 #> 2822 9.3 7 1866 1866-07-02 12:00:00 bone 1411 #> 2823 12.7 8 1866 1866-08-01 22:00:01 blood 1412 #> 2824 12.7 8 1866 1866-08-01 22:00:01 bone 1412 #> 2825 7.3 9 1866 1866-09-01 08:00:01 blood 1413 #> 2826 7.3 9 1866 1866-09-01 08:00:01 bone 1413 #> 2827 14.1 10 1866 1866-10-01 18:00:00 blood 1414 #> 2828 14.1 10 1866 1866-10-01 18:00:00 bone 1414 #> 2829 9.0 11 1866 1866-11-01 04:00:01 blood 1415 #> 2830 9.0 11 1866 1866-11-01 04:00:01 bone 1415 #> 2831 1.5 12 1866 1866-12-01 14:00:01 blood 1416 #> 2832 1.5 12 1866 1866-12-01 14:00:01 bone 1416 #> 2833 0.0 1 1867 1867-01-01 00:00:00 blood 1417 #> 2834 0.0 1 1867 1867-01-01 00:00:00 bone 1417 #> 2835 0.7 2 1867 1867-01-31 10:00:01 blood 1418 #> 2836 0.7 2 1867 1867-01-31 10:00:01 bone 1418 #> 2837 9.2 3 1867 1867-03-02 20:00:01 blood 1419 #> 2838 9.2 3 1867 1867-03-02 20:00:01 bone 1419 #> 2839 5.1 4 1867 1867-04-02 06:00:00 blood 1420 #> 2840 5.1 4 1867 1867-04-02 06:00:00 bone 1420 #> 2841 2.9 5 1867 1867-05-02 16:00:01 blood 1421 #> 2842 2.9 5 1867 1867-05-02 16:00:01 bone 1421 #> 2843 1.5 6 1867 1867-06-02 02:00:01 blood 1422 #> 2844 1.5 6 1867 1867-06-02 02:00:01 bone 1422 #> 2845 5.0 7 1867 1867-07-02 12:00:00 blood 1423 #> 2846 5.0 7 1867 1867-07-02 12:00:00 bone 1423 #> 2847 4.9 8 1867 1867-08-01 22:00:01 blood 1424 #> 2848 4.9 8 1867 1867-08-01 22:00:01 bone 1424 #> 2849 9.8 9 1867 1867-09-01 08:00:01 blood 1425 #> 2850 9.8 9 1867 1867-09-01 08:00:01 bone 1425 #> 2851 13.5 10 1867 1867-10-01 18:00:00 blood 1426 #> 2852 13.5 10 1867 1867-10-01 18:00:00 bone 1426 #> 2853 9.3 11 1867 1867-11-01 04:00:01 blood 1427 #> 2854 9.3 11 1867 1867-11-01 04:00:01 bone 1427 #> 2855 25.2 12 1867 1867-12-01 14:00:01 blood 1428 #> 2856 25.2 12 1867 1867-12-01 14:00:01 bone 1428 #> 2857 15.6 1 1868 1868-01-01 00:00:00 blood 1429 #> 2858 15.6 1 1868 1868-01-01 00:00:00 bone 1429 #> 2859 15.8 2 1868 1868-01-31 12:00:01 blood 1430 #> 2860 15.8 2 1868 1868-01-31 12:00:01 bone 1430 #> 2861 26.5 3 1868 1868-03-02 00:00:01 blood 1431 #> 2862 26.5 3 1868 1868-03-02 00:00:01 bone 1431 #> 2863 36.6 4 1868 1868-04-01 12:00:00 blood 1432 #> 2864 36.6 4 1868 1868-04-01 12:00:00 bone 1432 #> 2865 26.7 5 1868 1868-05-02 00:00:01 blood 1433 #> 2866 26.7 5 1868 1868-05-02 00:00:01 bone 1433 #> 2867 31.1 6 1868 1868-06-01 12:00:01 blood 1434 #> 2868 31.1 6 1868 1868-06-01 12:00:01 bone 1434 #> 2869 28.6 7 1868 1868-07-02 00:00:00 blood 1435 #> 2870 28.6 7 1868 1868-07-02 00:00:00 bone 1435 #> 2871 34.4 8 1868 1868-08-01 12:00:01 blood 1436 #> 2872 34.4 8 1868 1868-08-01 12:00:01 bone 1436 #> 2873 43.8 9 1868 1868-09-01 00:00:01 blood 1437 #> 2874 43.8 9 1868 1868-09-01 00:00:01 bone 1437 #> 2875 61.7 10 1868 1868-10-01 12:00:00 blood 1438 #> 2876 61.7 10 1868 1868-10-01 12:00:00 bone 1438 #> 2877 59.1 11 1868 1868-11-01 00:00:01 blood 1439 #> 2878 59.1 11 1868 1868-11-01 00:00:01 bone 1439 #> 2879 67.6 12 1868 1868-12-01 12:00:01 blood 1440 #> 2880 67.6 12 1868 1868-12-01 12:00:01 bone 1440 #> 2881 60.9 1 1869 1869-01-01 00:00:00 blood 1441 #> 2882 60.9 1 1869 1869-01-01 00:00:00 bone 1441 #> 2883 59.3 2 1869 1869-01-31 10:00:01 blood 1442 #> 2884 59.3 2 1869 1869-01-31 10:00:01 bone 1442 #> 2885 52.7 3 1869 1869-03-02 20:00:01 blood 1443 #> 2886 52.7 3 1869 1869-03-02 20:00:01 bone 1443 #> 2887 41.0 4 1869 1869-04-02 06:00:00 blood 1444 #> 2888 41.0 4 1869 1869-04-02 06:00:00 bone 1444 #> 2889 104.0 5 1869 1869-05-02 16:00:01 blood 1445 #> 2890 104.0 5 1869 1869-05-02 16:00:01 bone 1445 #> 2891 108.4 6 1869 1869-06-02 02:00:01 blood 1446 #> 2892 108.4 6 1869 1869-06-02 02:00:01 bone 1446 #> 2893 59.2 7 1869 1869-07-02 12:00:00 blood 1447 #> 2894 59.2 7 1869 1869-07-02 12:00:00 bone 1447 #> 2895 79.6 8 1869 1869-08-01 22:00:01 blood 1448 #> 2896 79.6 8 1869 1869-08-01 22:00:01 bone 1448 #> 2897 80.6 9 1869 1869-09-01 08:00:01 blood 1449 #> 2898 80.6 9 1869 1869-09-01 08:00:01 bone 1449 #> 2899 59.4 10 1869 1869-10-01 18:00:00 blood 1450 #> 2900 59.4 10 1869 1869-10-01 18:00:00 bone 1450 #> 2901 77.4 11 1869 1869-11-01 04:00:01 blood 1451 #> 2902 77.4 11 1869 1869-11-01 04:00:01 bone 1451 #> 2903 104.3 12 1869 1869-12-01 14:00:01 blood 1452 #> 2904 104.3 12 1869 1869-12-01 14:00:01 bone 1452 #> 2905 77.3 1 1870 1870-01-01 00:00:00 blood 1453 #> 2906 77.3 1 1870 1870-01-01 00:00:00 bone 1453 #> 2907 114.9 2 1870 1870-01-31 10:00:01 blood 1454 #> 2908 114.9 2 1870 1870-01-31 10:00:01 bone 1454 #> 2909 159.4 3 1870 1870-03-02 20:00:01 blood 1455 #> 2910 159.4 3 1870 1870-03-02 20:00:01 bone 1455 #> 2911 160.0 4 1870 1870-04-02 06:00:00 blood 1456 #> 2912 160.0 4 1870 1870-04-02 06:00:00 bone 1456 #> 2913 176.0 5 1870 1870-05-02 16:00:01 blood 1457 #> 2914 176.0 5 1870 1870-05-02 16:00:01 bone 1457 #> 2915 135.6 6 1870 1870-06-02 02:00:01 blood 1458 #> 2916 135.6 6 1870 1870-06-02 02:00:01 bone 1458 #> 2917 132.4 7 1870 1870-07-02 12:00:00 blood 1459 #> 2918 132.4 7 1870 1870-07-02 12:00:00 bone 1459 #> 2919 153.8 8 1870 1870-08-01 22:00:01 blood 1460 #> 2920 153.8 8 1870 1870-08-01 22:00:01 bone 1460 #> 2921 136.0 9 1870 1870-09-01 08:00:01 blood 1461 #> 2922 136.0 9 1870 1870-09-01 08:00:01 bone 1461 #> 2923 146.4 10 1870 1870-10-01 18:00:00 blood 1462 #> 2924 146.4 10 1870 1870-10-01 18:00:00 bone 1462 #> 2925 147.5 11 1870 1870-11-01 04:00:01 blood 1463 #> 2926 147.5 11 1870 1870-11-01 04:00:01 bone 1463 #> 2927 130.0 12 1870 1870-12-01 14:00:01 blood 1464 #> 2928 130.0 12 1870 1870-12-01 14:00:01 bone 1464 #> 2929 88.3 1 1871 1871-01-01 00:00:00 blood 1465 #> 2930 88.3 1 1871 1871-01-01 00:00:00 bone 1465 #> 2931 125.3 2 1871 1871-01-31 10:00:01 blood 1466 #> 2932 125.3 2 1871 1871-01-31 10:00:01 bone 1466 #> 2933 143.2 3 1871 1871-03-02 20:00:01 blood 1467 #> 2934 143.2 3 1871 1871-03-02 20:00:01 bone 1467 #> 2935 162.4 4 1871 1871-04-02 06:00:00 blood 1468 #> 2936 162.4 4 1871 1871-04-02 06:00:00 bone 1468 #> 2937 145.5 5 1871 1871-05-02 16:00:01 blood 1469 #> 2938 145.5 5 1871 1871-05-02 16:00:01 bone 1469 #> 2939 91.7 6 1871 1871-06-02 02:00:01 blood 1470 #> 2940 91.7 6 1871 1871-06-02 02:00:01 bone 1470 #> 2941 103.0 7 1871 1871-07-02 12:00:00 blood 1471 #> 2942 103.0 7 1871 1871-07-02 12:00:00 bone 1471 #> 2943 110.0 8 1871 1871-08-01 22:00:01 blood 1472 #> 2944 110.0 8 1871 1871-08-01 22:00:01 bone 1472 #> 2945 80.3 9 1871 1871-09-01 08:00:01 blood 1473 #> 2946 80.3 9 1871 1871-09-01 08:00:01 bone 1473 #> 2947 89.0 10 1871 1871-10-01 18:00:00 blood 1474 #> 2948 89.0 10 1871 1871-10-01 18:00:00 bone 1474 #> 2949 105.4 11 1871 1871-11-01 04:00:01 blood 1475 #> 2950 105.4 11 1871 1871-11-01 04:00:01 bone 1475 #> 2951 90.3 12 1871 1871-12-01 14:00:01 blood 1476 #> 2952 90.3 12 1871 1871-12-01 14:00:01 bone 1476 #> 2953 79.5 1 1872 1872-01-01 00:00:00 blood 1477 #> 2954 79.5 1 1872 1872-01-01 00:00:00 bone 1477 #> 2955 120.1 2 1872 1872-01-31 12:00:01 blood 1478 #> 2956 120.1 2 1872 1872-01-31 12:00:01 bone 1478 #> 2957 88.4 3 1872 1872-03-02 00:00:01 blood 1479 #> 2958 88.4 3 1872 1872-03-02 00:00:01 bone 1479 #> 2959 102.1 4 1872 1872-04-01 12:00:00 blood 1480 #> 2960 102.1 4 1872 1872-04-01 12:00:00 bone 1480 #> 2961 107.6 5 1872 1872-05-02 00:00:01 blood 1481 #> 2962 107.6 5 1872 1872-05-02 00:00:01 bone 1481 #> 2963 109.9 6 1872 1872-06-01 12:00:01 blood 1482 #> 2964 109.9 6 1872 1872-06-01 12:00:01 bone 1482 #> 2965 105.5 7 1872 1872-07-02 00:00:00 blood 1483 #> 2966 105.5 7 1872 1872-07-02 00:00:00 bone 1483 #> 2967 92.9 8 1872 1872-08-01 12:00:01 blood 1484 #> 2968 92.9 8 1872 1872-08-01 12:00:01 bone 1484 #> 2969 114.6 9 1872 1872-09-01 00:00:01 blood 1485 #> 2970 114.6 9 1872 1872-09-01 00:00:01 bone 1485 #> 2971 103.5 10 1872 1872-10-01 12:00:00 blood 1486 #> 2972 103.5 10 1872 1872-10-01 12:00:00 bone 1486 #> 2973 112.0 11 1872 1872-11-01 00:00:01 blood 1487 #> 2974 112.0 11 1872 1872-11-01 00:00:01 bone 1487 #> 2975 83.9 12 1872 1872-12-01 12:00:01 blood 1488 #> 2976 83.9 12 1872 1872-12-01 12:00:01 bone 1488 #> 2977 86.7 1 1873 1873-01-01 00:00:00 blood 1489 #> 2978 86.7 1 1873 1873-01-01 00:00:00 bone 1489 #> 2979 107.0 2 1873 1873-01-31 10:00:01 blood 1490 #> 2980 107.0 2 1873 1873-01-31 10:00:01 bone 1490 #> 2981 98.3 3 1873 1873-03-02 20:00:01 blood 1491 #> 2982 98.3 3 1873 1873-03-02 20:00:01 bone 1491 #> 2983 76.2 4 1873 1873-04-02 06:00:00 blood 1492 #> 2984 76.2 4 1873 1873-04-02 06:00:00 bone 1492 #> 2985 47.9 5 1873 1873-05-02 16:00:01 blood 1493 #> 2986 47.9 5 1873 1873-05-02 16:00:01 bone 1493 #> 2987 44.8 6 1873 1873-06-02 02:00:01 blood 1494 #> 2988 44.8 6 1873 1873-06-02 02:00:01 bone 1494 #> 2989 66.9 7 1873 1873-07-02 12:00:00 blood 1495 #> 2990 66.9 7 1873 1873-07-02 12:00:00 bone 1495 #> 2991 68.2 8 1873 1873-08-01 22:00:01 blood 1496 #> 2992 68.2 8 1873 1873-08-01 22:00:01 bone 1496 #> 2993 47.5 9 1873 1873-09-01 08:00:01 blood 1497 #> 2994 47.5 9 1873 1873-09-01 08:00:01 bone 1497 #> 2995 47.4 10 1873 1873-10-01 18:00:00 blood 1498 #> 2996 47.4 10 1873 1873-10-01 18:00:00 bone 1498 #> 2997 55.4 11 1873 1873-11-01 04:00:01 blood 1499 #> 2998 55.4 11 1873 1873-11-01 04:00:01 bone 1499 #> 2999 49.2 12 1873 1873-12-01 14:00:01 blood 1500 #> 3000 49.2 12 1873 1873-12-01 14:00:01 bone 1500 #> 3001 60.8 1 1874 1874-01-01 00:00:00 blood 1501 #> 3002 60.8 1 1874 1874-01-01 00:00:00 bone 1501 #> 3003 64.2 2 1874 1874-01-31 10:00:01 blood 1502 #> 3004 64.2 2 1874 1874-01-31 10:00:01 bone 1502 #> 3005 46.4 3 1874 1874-03-02 20:00:01 blood 1503 #> 3006 46.4 3 1874 1874-03-02 20:00:01 bone 1503 #> 3007 32.0 4 1874 1874-04-02 06:00:00 blood 1504 #> 3008 32.0 4 1874 1874-04-02 06:00:00 bone 1504 #> 3009 44.6 5 1874 1874-05-02 16:00:01 blood 1505 #> 3010 44.6 5 1874 1874-05-02 16:00:01 bone 1505 #> 3011 38.2 6 1874 1874-06-02 02:00:01 blood 1506 #> 3012 38.2 6 1874 1874-06-02 02:00:01 bone 1506 #> 3013 67.8 7 1874 1874-07-02 12:00:00 blood 1507 #> 3014 67.8 7 1874 1874-07-02 12:00:00 bone 1507 #> 3015 61.3 8 1874 1874-08-01 22:00:01 blood 1508 #> 3016 61.3 8 1874 1874-08-01 22:00:01 bone 1508 #> 3017 28.0 9 1874 1874-09-01 08:00:01 blood 1509 #> 3018 28.0 9 1874 1874-09-01 08:00:01 bone 1509 #> 3019 34.3 10 1874 1874-10-01 18:00:00 blood 1510 #> 3020 34.3 10 1874 1874-10-01 18:00:00 bone 1510 #> 3021 28.9 11 1874 1874-11-01 04:00:01 blood 1511 #> 3022 28.9 11 1874 1874-11-01 04:00:01 bone 1511 #> 3023 29.3 12 1874 1874-12-01 14:00:01 blood 1512 #> 3024 29.3 12 1874 1874-12-01 14:00:01 bone 1512 #> 3025 14.6 1 1875 1875-01-01 00:00:00 blood 1513 #> 3026 14.6 1 1875 1875-01-01 00:00:00 bone 1513 #> 3027 22.2 2 1875 1875-01-31 10:00:01 blood 1514 #> 3028 22.2 2 1875 1875-01-31 10:00:01 bone 1514 #> 3029 33.8 3 1875 1875-03-02 20:00:01 blood 1515 #> 3030 33.8 3 1875 1875-03-02 20:00:01 bone 1515 #> 3031 29.1 4 1875 1875-04-02 06:00:00 blood 1516 #> 3032 29.1 4 1875 1875-04-02 06:00:00 bone 1516 #> 3033 11.5 5 1875 1875-05-02 16:00:01 blood 1517 #> 3034 11.5 5 1875 1875-05-02 16:00:01 bone 1517 #> 3035 23.9 6 1875 1875-06-02 02:00:01 blood 1518 #> 3036 23.9 6 1875 1875-06-02 02:00:01 bone 1518 #> 3037 12.5 7 1875 1875-07-02 12:00:00 blood 1519 #> 3038 12.5 7 1875 1875-07-02 12:00:00 bone 1519 #> 3039 14.6 8 1875 1875-08-01 22:00:01 blood 1520 #> 3040 14.6 8 1875 1875-08-01 22:00:01 bone 1520 #> 3041 2.4 9 1875 1875-09-01 08:00:01 blood 1521 #> 3042 2.4 9 1875 1875-09-01 08:00:01 bone 1521 #> 3043 12.7 10 1875 1875-10-01 18:00:00 blood 1522 #> 3044 12.7 10 1875 1875-10-01 18:00:00 bone 1522 #> 3045 17.7 11 1875 1875-11-01 04:00:01 blood 1523 #> 3046 17.7 11 1875 1875-11-01 04:00:01 bone 1523 #> 3047 9.9 12 1875 1875-12-01 14:00:01 blood 1524 #> 3048 9.9 12 1875 1875-12-01 14:00:01 bone 1524 #> 3049 14.3 1 1876 1876-01-01 00:00:00 blood 1525 #> 3050 14.3 1 1876 1876-01-01 00:00:00 bone 1525 #> 3051 15.0 2 1876 1876-01-31 12:00:01 blood 1526 #> 3052 15.0 2 1876 1876-01-31 12:00:01 bone 1526 #> 3053 31.2 3 1876 1876-03-02 00:00:01 blood 1527 #> 3054 31.2 3 1876 1876-03-02 00:00:01 bone 1527 #> 3055 2.3 4 1876 1876-04-01 12:00:00 blood 1528 #> 3056 2.3 4 1876 1876-04-01 12:00:00 bone 1528 #> 3057 5.1 5 1876 1876-05-02 00:00:01 blood 1529 #> 3058 5.1 5 1876 1876-05-02 00:00:01 bone 1529 #> 3059 1.6 6 1876 1876-06-01 12:00:01 blood 1530 #> 3060 1.6 6 1876 1876-06-01 12:00:01 bone 1530 #> 3061 15.2 7 1876 1876-07-02 00:00:00 blood 1531 #> 3062 15.2 7 1876 1876-07-02 00:00:00 bone 1531 #> 3063 8.8 8 1876 1876-08-01 12:00:01 blood 1532 #> 3064 8.8 8 1876 1876-08-01 12:00:01 bone 1532 #> 3065 9.9 9 1876 1876-09-01 00:00:01 blood 1533 #> 3066 9.9 9 1876 1876-09-01 00:00:01 bone 1533 #> 3067 14.3 10 1876 1876-10-01 12:00:00 blood 1534 #> 3068 14.3 10 1876 1876-10-01 12:00:00 bone 1534 #> 3069 9.9 11 1876 1876-11-01 00:00:01 blood 1535 #> 3070 9.9 11 1876 1876-11-01 00:00:01 bone 1535 #> 3071 8.2 12 1876 1876-12-01 12:00:01 blood 1536 #> 3072 8.2 12 1876 1876-12-01 12:00:01 bone 1536 #> 3073 24.4 1 1877 1877-01-01 00:00:00 blood 1537 #> 3074 24.4 1 1877 1877-01-01 00:00:00 bone 1537 #> 3075 8.7 2 1877 1877-01-31 10:00:01 blood 1538 #> 3076 8.7 2 1877 1877-01-31 10:00:01 bone 1538 #> 3077 11.7 3 1877 1877-03-02 20:00:01 blood 1539 #> 3078 11.7 3 1877 1877-03-02 20:00:01 bone 1539 #> 3079 15.8 4 1877 1877-04-02 06:00:00 blood 1540 #> 3080 15.8 4 1877 1877-04-02 06:00:00 bone 1540 #> 3081 21.2 5 1877 1877-05-02 16:00:01 blood 1541 #> 3082 21.2 5 1877 1877-05-02 16:00:01 bone 1541 #> 3083 13.4 6 1877 1877-06-02 02:00:01 blood 1542 #> 3084 13.4 6 1877 1877-06-02 02:00:01 bone 1542 #> 3085 5.9 7 1877 1877-07-02 12:00:00 blood 1543 #> 3086 5.9 7 1877 1877-07-02 12:00:00 bone 1543 #> 3087 6.3 8 1877 1877-08-01 22:00:01 blood 1544 #> 3088 6.3 8 1877 1877-08-01 22:00:01 bone 1544 #> 3089 16.4 9 1877 1877-09-01 08:00:01 blood 1545 #> 3090 16.4 9 1877 1877-09-01 08:00:01 bone 1545 #> 3091 6.7 10 1877 1877-10-01 18:00:00 blood 1546 #> 3092 6.7 10 1877 1877-10-01 18:00:00 bone 1546 #> 3093 14.5 11 1877 1877-11-01 04:00:01 blood 1547 #> 3094 14.5 11 1877 1877-11-01 04:00:01 bone 1547 #> 3095 2.3 12 1877 1877-12-01 14:00:01 blood 1548 #> 3096 2.3 12 1877 1877-12-01 14:00:01 bone 1548 #> 3097 3.3 1 1878 1878-01-01 00:00:00 blood 1549 #> 3098 3.3 1 1878 1878-01-01 00:00:00 bone 1549 #> 3099 6.0 2 1878 1878-01-31 10:00:01 blood 1550 #> 3100 6.0 2 1878 1878-01-31 10:00:01 bone 1550 #> 3101 7.8 3 1878 1878-03-02 20:00:01 blood 1551 #> 3102 7.8 3 1878 1878-03-02 20:00:01 bone 1551 #> 3103 0.1 4 1878 1878-04-02 06:00:00 blood 1552 #> 3104 0.1 4 1878 1878-04-02 06:00:00 bone 1552 #> 3105 5.8 5 1878 1878-05-02 16:00:01 blood 1553 #> 3106 5.8 5 1878 1878-05-02 16:00:01 bone 1553 #> 3107 6.4 6 1878 1878-06-02 02:00:01 blood 1554 #> 3108 6.4 6 1878 1878-06-02 02:00:01 bone 1554 #> 3109 0.1 7 1878 1878-07-02 12:00:00 blood 1555 #> 3110 0.1 7 1878 1878-07-02 12:00:00 bone 1555 #> 3111 0.0 8 1878 1878-08-01 22:00:01 blood 1556 #> 3112 0.0 8 1878 1878-08-01 22:00:01 bone 1556 #> 3113 5.3 9 1878 1878-09-01 08:00:01 blood 1557 #> 3114 5.3 9 1878 1878-09-01 08:00:01 bone 1557 #> 3115 1.1 10 1878 1878-10-01 18:00:00 blood 1558 #> 3116 1.1 10 1878 1878-10-01 18:00:00 bone 1558 #> 3117 4.1 11 1878 1878-11-01 04:00:01 blood 1559 #> 3118 4.1 11 1878 1878-11-01 04:00:01 bone 1559 #> 3119 0.5 12 1878 1878-12-01 14:00:01 blood 1560 #> 3120 0.5 12 1878 1878-12-01 14:00:01 bone 1560 #> 3121 0.8 1 1879 1879-01-01 00:00:00 blood 1561 #> 3122 0.8 1 1879 1879-01-01 00:00:00 bone 1561 #> 3123 0.6 2 1879 1879-01-31 10:00:01 blood 1562 #> 3124 0.6 2 1879 1879-01-31 10:00:01 bone 1562 #> 3125 0.0 3 1879 1879-03-02 20:00:01 blood 1563 #> 3126 0.0 3 1879 1879-03-02 20:00:01 bone 1563 #> 3127 6.2 4 1879 1879-04-02 06:00:00 blood 1564 #> 3128 6.2 4 1879 1879-04-02 06:00:00 bone 1564 #> 3129 2.4 5 1879 1879-05-02 16:00:01 blood 1565 #> 3130 2.4 5 1879 1879-05-02 16:00:01 bone 1565 #> 3131 4.8 6 1879 1879-06-02 02:00:01 blood 1566 #> 3132 4.8 6 1879 1879-06-02 02:00:01 bone 1566 #> 3133 7.5 7 1879 1879-07-02 12:00:00 blood 1567 #> 3134 7.5 7 1879 1879-07-02 12:00:00 bone 1567 #> 3135 10.7 8 1879 1879-08-01 22:00:01 blood 1568 #> 3136 10.7 8 1879 1879-08-01 22:00:01 bone 1568 #> 3137 6.1 9 1879 1879-09-01 08:00:01 blood 1569 #> 3138 6.1 9 1879 1879-09-01 08:00:01 bone 1569 #> 3139 12.3 10 1879 1879-10-01 18:00:00 blood 1570 #> 3140 12.3 10 1879 1879-10-01 18:00:00 bone 1570 #> 3141 12.9 11 1879 1879-11-01 04:00:01 blood 1571 #> 3142 12.9 11 1879 1879-11-01 04:00:01 bone 1571 #> 3143 7.2 12 1879 1879-12-01 14:00:01 blood 1572 #> 3144 7.2 12 1879 1879-12-01 14:00:01 bone 1572 #> 3145 24.0 1 1880 1880-01-01 00:00:00 blood 1573 #> 3146 24.0 1 1880 1880-01-01 00:00:00 bone 1573 #> 3147 27.5 2 1880 1880-01-31 12:00:01 blood 1574 #> 3148 27.5 2 1880 1880-01-31 12:00:01 bone 1574 #> 3149 19.5 3 1880 1880-03-02 00:00:01 blood 1575 #> 3150 19.5 3 1880 1880-03-02 00:00:01 bone 1575 #> 3151 19.3 4 1880 1880-04-01 12:00:00 blood 1576 #> 3152 19.3 4 1880 1880-04-01 12:00:00 bone 1576 #> 3153 23.5 5 1880 1880-05-02 00:00:01 blood 1577 #> 3154 23.5 5 1880 1880-05-02 00:00:01 bone 1577 #> 3155 34.1 6 1880 1880-06-01 12:00:01 blood 1578 #> 3156 34.1 6 1880 1880-06-01 12:00:01 bone 1578 #> 3157 21.9 7 1880 1880-07-02 00:00:00 blood 1579 #> 3158 21.9 7 1880 1880-07-02 00:00:00 bone 1579 #> 3159 48.1 8 1880 1880-08-01 12:00:01 blood 1580 #> 3160 48.1 8 1880 1880-08-01 12:00:01 bone 1580 #> 3161 66.0 9 1880 1880-09-01 00:00:01 blood 1581 #> 3162 66.0 9 1880 1880-09-01 00:00:01 bone 1581 #> 3163 43.0 10 1880 1880-10-01 12:00:00 blood 1582 #> 3164 43.0 10 1880 1880-10-01 12:00:00 bone 1582 #> 3165 30.7 11 1880 1880-11-01 00:00:01 blood 1583 #> 3166 30.7 11 1880 1880-11-01 00:00:01 bone 1583 #> 3167 29.6 12 1880 1880-12-01 12:00:01 blood 1584 #> 3168 29.6 12 1880 1880-12-01 12:00:01 bone 1584 #> 3169 36.4 1 1881 1881-01-01 00:00:00 blood 1585 #> 3170 36.4 1 1881 1881-01-01 00:00:00 bone 1585 #> 3171 53.2 2 1881 1881-01-31 10:00:01 blood 1586 #> 3172 53.2 2 1881 1881-01-31 10:00:01 bone 1586 #> 3173 51.5 3 1881 1881-03-02 20:00:01 blood 1587 #> 3174 51.5 3 1881 1881-03-02 20:00:01 bone 1587 #> 3175 51.7 4 1881 1881-04-02 06:00:00 blood 1588 #> 3176 51.7 4 1881 1881-04-02 06:00:00 bone 1588 #> 3177 43.5 5 1881 1881-05-02 16:00:01 blood 1589 #> 3178 43.5 5 1881 1881-05-02 16:00:01 bone 1589 #> 3179 60.5 6 1881 1881-06-02 02:00:01 blood 1590 #> 3180 60.5 6 1881 1881-06-02 02:00:01 bone 1590 #> 3181 76.9 7 1881 1881-07-02 12:00:00 blood 1591 #> 3182 76.9 7 1881 1881-07-02 12:00:00 bone 1591 #> 3183 58.0 8 1881 1881-08-01 22:00:01 blood 1592 #> 3184 58.0 8 1881 1881-08-01 22:00:01 bone 1592 #> 3185 53.2 9 1881 1881-09-01 08:00:01 blood 1593 #> 3186 53.2 9 1881 1881-09-01 08:00:01 bone 1593 #> 3187 64.0 10 1881 1881-10-01 18:00:00 blood 1594 #> 3188 64.0 10 1881 1881-10-01 18:00:00 bone 1594 #> 3189 54.8 11 1881 1881-11-01 04:00:01 blood 1595 #> 3190 54.8 11 1881 1881-11-01 04:00:01 bone 1595 #> 3191 47.3 12 1881 1881-12-01 14:00:01 blood 1596 #> 3192 47.3 12 1881 1881-12-01 14:00:01 bone 1596 #> 3193 45.0 1 1882 1882-01-01 00:00:00 blood 1597 #> 3194 45.0 1 1882 1882-01-01 00:00:00 bone 1597 #> 3195 69.3 2 1882 1882-01-31 10:00:01 blood 1598 #> 3196 69.3 2 1882 1882-01-31 10:00:01 bone 1598 #> 3197 67.5 3 1882 1882-03-02 20:00:01 blood 1599 #> 3198 67.5 3 1882 1882-03-02 20:00:01 bone 1599 #> 3199 95.8 4 1882 1882-04-02 06:00:00 blood 1600 #> 3200 95.8 4 1882 1882-04-02 06:00:00 bone 1600 #> 3201 64.1 5 1882 1882-05-02 16:00:01 blood 1601 #> 3202 64.1 5 1882 1882-05-02 16:00:01 bone 1601 #> 3203 45.2 6 1882 1882-06-02 02:00:01 blood 1602 #> 3204 45.2 6 1882 1882-06-02 02:00:01 bone 1602 #> 3205 45.4 7 1882 1882-07-02 12:00:00 blood 1603 #> 3206 45.4 7 1882 1882-07-02 12:00:00 bone 1603 #> 3207 40.4 8 1882 1882-08-01 22:00:01 blood 1604 #> 3208 40.4 8 1882 1882-08-01 22:00:01 bone 1604 #> 3209 57.7 9 1882 1882-09-01 08:00:01 blood 1605 #> 3210 57.7 9 1882 1882-09-01 08:00:01 bone 1605 #> 3211 59.2 10 1882 1882-10-01 18:00:00 blood 1606 #> 3212 59.2 10 1882 1882-10-01 18:00:00 bone 1606 #> 3213 84.4 11 1882 1882-11-01 04:00:01 blood 1607 #> 3214 84.4 11 1882 1882-11-01 04:00:01 bone 1607 #> 3215 41.8 12 1882 1882-12-01 14:00:01 blood 1608 #> 3216 41.8 12 1882 1882-12-01 14:00:01 bone 1608 #> 3217 60.6 1 1883 1883-01-01 00:00:00 blood 1609 #> 3218 60.6 1 1883 1883-01-01 00:00:00 bone 1609 #> 3219 46.9 2 1883 1883-01-31 10:00:01 blood 1610 #> 3220 46.9 2 1883 1883-01-31 10:00:01 bone 1610 #> 3221 42.8 3 1883 1883-03-02 20:00:01 blood 1611 #> 3222 42.8 3 1883 1883-03-02 20:00:01 bone 1611 #> 3223 82.1 4 1883 1883-04-02 06:00:00 blood 1612 #> 3224 82.1 4 1883 1883-04-02 06:00:00 bone 1612 #> 3225 32.1 5 1883 1883-05-02 16:00:01 blood 1613 #> 3226 32.1 5 1883 1883-05-02 16:00:01 bone 1613 #> 3227 76.5 6 1883 1883-06-02 02:00:01 blood 1614 #> 3228 76.5 6 1883 1883-06-02 02:00:01 bone 1614 #> 3229 80.6 7 1883 1883-07-02 12:00:00 blood 1615 #> 3230 80.6 7 1883 1883-07-02 12:00:00 bone 1615 #> 3231 46.0 8 1883 1883-08-01 22:00:01 blood 1616 #> 3232 46.0 8 1883 1883-08-01 22:00:01 bone 1616 #> 3233 52.6 9 1883 1883-09-01 08:00:01 blood 1617 #> 3234 52.6 9 1883 1883-09-01 08:00:01 bone 1617 #> 3235 83.8 10 1883 1883-10-01 18:00:00 blood 1618 #> 3236 83.8 10 1883 1883-10-01 18:00:00 bone 1618 #> 3237 84.5 11 1883 1883-11-01 04:00:01 blood 1619 #> 3238 84.5 11 1883 1883-11-01 04:00:01 bone 1619 #> 3239 75.9 12 1883 1883-12-01 14:00:01 blood 1620 #> 3240 75.9 12 1883 1883-12-01 14:00:01 bone 1620 #> 3241 91.5 1 1884 1884-01-01 00:00:00 blood 1621 #> 3242 91.5 1 1884 1884-01-01 00:00:00 bone 1621 #> 3243 86.9 2 1884 1884-01-31 12:00:01 blood 1622 #> 3244 86.9 2 1884 1884-01-31 12:00:01 bone 1622 #> 3245 86.8 3 1884 1884-03-02 00:00:01 blood 1623 #> 3246 86.8 3 1884 1884-03-02 00:00:01 bone 1623 #> 3247 76.1 4 1884 1884-04-01 12:00:00 blood 1624 #> 3248 76.1 4 1884 1884-04-01 12:00:00 bone 1624 #> 3249 66.5 5 1884 1884-05-02 00:00:01 blood 1625 #> 3250 66.5 5 1884 1884-05-02 00:00:01 bone 1625 #> 3251 51.2 6 1884 1884-06-01 12:00:01 blood 1626 #> 3252 51.2 6 1884 1884-06-01 12:00:01 bone 1626 #> 3253 53.1 7 1884 1884-07-02 00:00:00 blood 1627 #> 3254 53.1 7 1884 1884-07-02 00:00:00 bone 1627 #> 3255 55.8 8 1884 1884-08-01 12:00:01 blood 1628 #> 3256 55.8 8 1884 1884-08-01 12:00:01 bone 1628 #> 3257 61.9 9 1884 1884-09-01 00:00:01 blood 1629 #> 3258 61.9 9 1884 1884-09-01 00:00:01 bone 1629 #> 3259 47.8 10 1884 1884-10-01 12:00:00 blood 1630 #> 3260 47.8 10 1884 1884-10-01 12:00:00 bone 1630 #> 3261 36.6 11 1884 1884-11-01 00:00:01 blood 1631 #> 3262 36.6 11 1884 1884-11-01 00:00:01 bone 1631 #> 3263 47.2 12 1884 1884-12-01 12:00:01 blood 1632 #> 3264 47.2 12 1884 1884-12-01 12:00:01 bone 1632 #> 3265 42.8 1 1885 1885-01-01 00:00:00 blood 1633 #> 3266 42.8 1 1885 1885-01-01 00:00:00 bone 1633 #> 3267 71.8 2 1885 1885-01-31 10:00:01 blood 1634 #> 3268 71.8 2 1885 1885-01-31 10:00:01 bone 1634 #> 3269 49.8 3 1885 1885-03-02 20:00:01 blood 1635 #> 3270 49.8 3 1885 1885-03-02 20:00:01 bone 1635 #> 3271 55.0 4 1885 1885-04-02 06:00:00 blood 1636 #> 3272 55.0 4 1885 1885-04-02 06:00:00 bone 1636 #> 3273 73.0 5 1885 1885-05-02 16:00:01 blood 1637 #> 3274 73.0 5 1885 1885-05-02 16:00:01 bone 1637 #> 3275 83.7 6 1885 1885-06-02 02:00:01 blood 1638 #> 3276 83.7 6 1885 1885-06-02 02:00:01 bone 1638 #> 3277 66.5 7 1885 1885-07-02 12:00:00 blood 1639 #> 3278 66.5 7 1885 1885-07-02 12:00:00 bone 1639 #> 3279 50.0 8 1885 1885-08-01 22:00:01 blood 1640 #> 3280 50.0 8 1885 1885-08-01 22:00:01 bone 1640 #> 3281 39.6 9 1885 1885-09-01 08:00:01 blood 1641 #> 3282 39.6 9 1885 1885-09-01 08:00:01 bone 1641 #> 3283 38.7 10 1885 1885-10-01 18:00:00 blood 1642 #> 3284 38.7 10 1885 1885-10-01 18:00:00 bone 1642 #> 3285 33.3 11 1885 1885-11-01 04:00:01 blood 1643 #> 3286 33.3 11 1885 1885-11-01 04:00:01 bone 1643 #> 3287 21.7 12 1885 1885-12-01 14:00:01 blood 1644 #> 3288 21.7 12 1885 1885-12-01 14:00:01 bone 1644 #> 3289 29.9 1 1886 1886-01-01 00:00:00 blood 1645 #> 3290 29.9 1 1886 1886-01-01 00:00:00 bone 1645 #> 3291 25.9 2 1886 1886-01-31 10:00:01 blood 1646 #> 3292 25.9 2 1886 1886-01-31 10:00:01 bone 1646 #> 3293 57.3 3 1886 1886-03-02 20:00:01 blood 1647 #> 3294 57.3 3 1886 1886-03-02 20:00:01 bone 1647 #> 3295 43.7 4 1886 1886-04-02 06:00:00 blood 1648 #> 3296 43.7 4 1886 1886-04-02 06:00:00 bone 1648 #> 3297 30.7 5 1886 1886-05-02 16:00:01 blood 1649 #> 3298 30.7 5 1886 1886-05-02 16:00:01 bone 1649 #> 3299 27.1 6 1886 1886-06-02 02:00:01 blood 1650 #> 3300 27.1 6 1886 1886-06-02 02:00:01 bone 1650 #> 3301 30.3 7 1886 1886-07-02 12:00:00 blood 1651 #> 3302 30.3 7 1886 1886-07-02 12:00:00 bone 1651 #> 3303 16.9 8 1886 1886-08-01 22:00:01 blood 1652 #> 3304 16.9 8 1886 1886-08-01 22:00:01 bone 1652 #> 3305 21.4 9 1886 1886-09-01 08:00:01 blood 1653 #> 3306 21.4 9 1886 1886-09-01 08:00:01 bone 1653 #> 3307 8.6 10 1886 1886-10-01 18:00:00 blood 1654 #> 3308 8.6 10 1886 1886-10-01 18:00:00 bone 1654 #> 3309 0.3 11 1886 1886-11-01 04:00:01 blood 1655 #> 3310 0.3 11 1886 1886-11-01 04:00:01 bone 1655 #> 3311 12.4 12 1886 1886-12-01 14:00:01 blood 1656 #> 3312 12.4 12 1886 1886-12-01 14:00:01 bone 1656 #> 3313 10.3 1 1887 1887-01-01 00:00:00 blood 1657 #> 3314 10.3 1 1887 1887-01-01 00:00:00 bone 1657 #> 3315 13.2 2 1887 1887-01-31 10:00:01 blood 1658 #> 3316 13.2 2 1887 1887-01-31 10:00:01 bone 1658 #> 3317 4.2 3 1887 1887-03-02 20:00:01 blood 1659 #> 3318 4.2 3 1887 1887-03-02 20:00:01 bone 1659 #> 3319 6.9 4 1887 1887-04-02 06:00:00 blood 1660 #> 3320 6.9 4 1887 1887-04-02 06:00:00 bone 1660 #> 3321 20.0 5 1887 1887-05-02 16:00:01 blood 1661 #> 3322 20.0 5 1887 1887-05-02 16:00:01 bone 1661 #> 3323 15.7 6 1887 1887-06-02 02:00:01 blood 1662 #> 3324 15.7 6 1887 1887-06-02 02:00:01 bone 1662 #> 3325 23.3 7 1887 1887-07-02 12:00:00 blood 1663 #> 3326 23.3 7 1887 1887-07-02 12:00:00 bone 1663 #> 3327 21.4 8 1887 1887-08-01 22:00:01 blood 1664 #> 3328 21.4 8 1887 1887-08-01 22:00:01 bone 1664 #> 3329 7.4 9 1887 1887-09-01 08:00:01 blood 1665 #> 3330 7.4 9 1887 1887-09-01 08:00:01 bone 1665 #> 3331 6.6 10 1887 1887-10-01 18:00:00 blood 1666 #> 3332 6.6 10 1887 1887-10-01 18:00:00 bone 1666 #> 3333 6.9 11 1887 1887-11-01 04:00:01 blood 1667 #> 3334 6.9 11 1887 1887-11-01 04:00:01 bone 1667 #> 3335 20.7 12 1887 1887-12-01 14:00:01 blood 1668 #> 3336 20.7 12 1887 1887-12-01 14:00:01 bone 1668 #> 3337 12.7 1 1888 1888-01-01 00:00:00 blood 1669 #> 3338 12.7 1 1888 1888-01-01 00:00:00 bone 1669 #> 3339 7.1 2 1888 1888-01-31 12:00:01 blood 1670 #> 3340 7.1 2 1888 1888-01-31 12:00:01 bone 1670 #> 3341 7.8 3 1888 1888-03-02 00:00:01 blood 1671 #> 3342 7.8 3 1888 1888-03-02 00:00:01 bone 1671 #> 3343 5.1 4 1888 1888-04-01 12:00:00 blood 1672 #> 3344 5.1 4 1888 1888-04-01 12:00:00 bone 1672 #> 3345 7.0 5 1888 1888-05-02 00:00:01 blood 1673 #> 3346 7.0 5 1888 1888-05-02 00:00:01 bone 1673 #> 3347 7.1 6 1888 1888-06-01 12:00:01 blood 1674 #> 3348 7.1 6 1888 1888-06-01 12:00:01 bone 1674 #> 3349 3.1 7 1888 1888-07-02 00:00:00 blood 1675 #> 3350 3.1 7 1888 1888-07-02 00:00:00 bone 1675 #> 3351 2.8 8 1888 1888-08-01 12:00:01 blood 1676 #> 3352 2.8 8 1888 1888-08-01 12:00:01 bone 1676 #> 3353 8.8 9 1888 1888-09-01 00:00:01 blood 1677 #> 3354 8.8 9 1888 1888-09-01 00:00:01 bone 1677 #> 3355 2.1 10 1888 1888-10-01 12:00:00 blood 1678 #> 3356 2.1 10 1888 1888-10-01 12:00:00 bone 1678 #> 3357 10.7 11 1888 1888-11-01 00:00:01 blood 1679 #> 3358 10.7 11 1888 1888-11-01 00:00:01 bone 1679 #> 3359 6.7 12 1888 1888-12-01 12:00:01 blood 1680 #> 3360 6.7 12 1888 1888-12-01 12:00:01 bone 1680 #> 3361 0.8 1 1889 1889-01-01 00:00:00 blood 1681 #> 3362 0.8 1 1889 1889-01-01 00:00:00 bone 1681 #> 3363 8.5 2 1889 1889-01-31 10:00:01 blood 1682 #> 3364 8.5 2 1889 1889-01-31 10:00:01 bone 1682 #> 3365 7.0 3 1889 1889-03-02 20:00:01 blood 1683 #> 3366 7.0 3 1889 1889-03-02 20:00:01 bone 1683 #> 3367 4.3 4 1889 1889-04-02 06:00:00 blood 1684 #> 3368 4.3 4 1889 1889-04-02 06:00:00 bone 1684 #> 3369 2.4 5 1889 1889-05-02 16:00:01 blood 1685 #> 3370 2.4 5 1889 1889-05-02 16:00:01 bone 1685 #> 3371 6.4 6 1889 1889-06-02 02:00:01 blood 1686 #> 3372 6.4 6 1889 1889-06-02 02:00:01 bone 1686 #> 3373 9.7 7 1889 1889-07-02 12:00:00 blood 1687 #> 3374 9.7 7 1889 1889-07-02 12:00:00 bone 1687 #> 3375 20.6 8 1889 1889-08-01 22:00:01 blood 1688 #> 3376 20.6 8 1889 1889-08-01 22:00:01 bone 1688 #> 3377 6.5 9 1889 1889-09-01 08:00:01 blood 1689 #> 3378 6.5 9 1889 1889-09-01 08:00:01 bone 1689 #> 3379 2.1 10 1889 1889-10-01 18:00:00 blood 1690 #> 3380 2.1 10 1889 1889-10-01 18:00:00 bone 1690 #> 3381 0.2 11 1889 1889-11-01 04:00:01 blood 1691 #> 3382 0.2 11 1889 1889-11-01 04:00:01 bone 1691 #> 3383 6.7 12 1889 1889-12-01 14:00:01 blood 1692 #> 3384 6.7 12 1889 1889-12-01 14:00:01 bone 1692 #> 3385 5.3 1 1890 1890-01-01 00:00:00 blood 1693 #> 3386 5.3 1 1890 1890-01-01 00:00:00 bone 1693 #> 3387 0.6 2 1890 1890-01-31 10:00:01 blood 1694 #> 3388 0.6 2 1890 1890-01-31 10:00:01 bone 1694 #> 3389 5.1 3 1890 1890-03-02 20:00:01 blood 1695 #> 3390 5.1 3 1890 1890-03-02 20:00:01 bone 1695 #> 3391 1.6 4 1890 1890-04-02 06:00:00 blood 1696 #> 3392 1.6 4 1890 1890-04-02 06:00:00 bone 1696 #> 3393 4.8 5 1890 1890-05-02 16:00:01 blood 1697 #> 3394 4.8 5 1890 1890-05-02 16:00:01 bone 1697 #> 3395 1.3 6 1890 1890-06-02 02:00:01 blood 1698 #> 3396 1.3 6 1890 1890-06-02 02:00:01 bone 1698 #> 3397 11.6 7 1890 1890-07-02 12:00:00 blood 1699 #> 3398 11.6 7 1890 1890-07-02 12:00:00 bone 1699 #> 3399 8.5 8 1890 1890-08-01 22:00:01 blood 1700 #> 3400 8.5 8 1890 1890-08-01 22:00:01 bone 1700 #> 3401 17.2 9 1890 1890-09-01 08:00:01 blood 1701 #> 3402 17.2 9 1890 1890-09-01 08:00:01 bone 1701 #> 3403 11.2 10 1890 1890-10-01 18:00:00 blood 1702 #> 3404 11.2 10 1890 1890-10-01 18:00:00 bone 1702 #> 3405 9.6 11 1890 1890-11-01 04:00:01 blood 1703 #> 3406 9.6 11 1890 1890-11-01 04:00:01 bone 1703 #> 3407 7.8 12 1890 1890-12-01 14:00:01 blood 1704 #> 3408 7.8 12 1890 1890-12-01 14:00:01 bone 1704 #> 3409 13.5 1 1891 1891-01-01 00:00:00 blood 1705 #> 3410 13.5 1 1891 1891-01-01 00:00:00 bone 1705 #> 3411 22.2 2 1891 1891-01-31 10:00:01 blood 1706 #> 3412 22.2 2 1891 1891-01-31 10:00:01 bone 1706 #> 3413 10.4 3 1891 1891-03-02 20:00:01 blood 1707 #> 3414 10.4 3 1891 1891-03-02 20:00:01 bone 1707 #> 3415 20.5 4 1891 1891-04-02 06:00:00 blood 1708 #> 3416 20.5 4 1891 1891-04-02 06:00:00 bone 1708 #> 3417 41.1 5 1891 1891-05-02 16:00:01 blood 1709 #> 3418 41.1 5 1891 1891-05-02 16:00:01 bone 1709 #> 3419 48.3 6 1891 1891-06-02 02:00:01 blood 1710 #> 3420 48.3 6 1891 1891-06-02 02:00:01 bone 1710 #> 3421 58.8 7 1891 1891-07-02 12:00:00 blood 1711 #> 3422 58.8 7 1891 1891-07-02 12:00:00 bone 1711 #> 3423 33.2 8 1891 1891-08-01 22:00:01 blood 1712 #> 3424 33.2 8 1891 1891-08-01 22:00:01 bone 1712 #> 3425 53.8 9 1891 1891-09-01 08:00:01 blood 1713 #> 3426 53.8 9 1891 1891-09-01 08:00:01 bone 1713 #> 3427 51.5 10 1891 1891-10-01 18:00:00 blood 1714 #> 3428 51.5 10 1891 1891-10-01 18:00:00 bone 1714 #> 3429 41.9 11 1891 1891-11-01 04:00:01 blood 1715 #> 3430 41.9 11 1891 1891-11-01 04:00:01 bone 1715 #> 3431 32.3 12 1891 1891-12-01 14:00:01 blood 1716 #> 3432 32.3 12 1891 1891-12-01 14:00:01 bone 1716 #> 3433 69.1 1 1892 1892-01-01 00:00:00 blood 1717 #> 3434 69.1 1 1892 1892-01-01 00:00:00 bone 1717 #> 3435 75.6 2 1892 1892-01-31 12:00:01 blood 1718 #> 3436 75.6 2 1892 1892-01-31 12:00:01 bone 1718 #> 3437 49.9 3 1892 1892-03-02 00:00:01 blood 1719 #> 3438 49.9 3 1892 1892-03-02 00:00:01 bone 1719 #> 3439 69.6 4 1892 1892-04-01 12:00:00 blood 1720 #> 3440 69.6 4 1892 1892-04-01 12:00:00 bone 1720 #> 3441 79.6 5 1892 1892-05-02 00:00:01 blood 1721 #> 3442 79.6 5 1892 1892-05-02 00:00:01 bone 1721 #> 3443 76.3 6 1892 1892-06-01 12:00:01 blood 1722 #> 3444 76.3 6 1892 1892-06-01 12:00:01 bone 1722 #> 3445 76.8 7 1892 1892-07-02 00:00:00 blood 1723 #> 3446 76.8 7 1892 1892-07-02 00:00:00 bone 1723 #> 3447 101.4 8 1892 1892-08-01 12:00:01 blood 1724 #> 3448 101.4 8 1892 1892-08-01 12:00:01 bone 1724 #> 3449 62.8 9 1892 1892-09-01 00:00:01 blood 1725 #> 3450 62.8 9 1892 1892-09-01 00:00:01 bone 1725 #> 3451 70.5 10 1892 1892-10-01 12:00:00 blood 1726 #> 3452 70.5 10 1892 1892-10-01 12:00:00 bone 1726 #> 3453 65.4 11 1892 1892-11-01 00:00:01 blood 1727 #> 3454 65.4 11 1892 1892-11-01 00:00:01 bone 1727 #> 3455 78.6 12 1892 1892-12-01 12:00:01 blood 1728 #> 3456 78.6 12 1892 1892-12-01 12:00:01 bone 1728 #> 3457 75.0 1 1893 1893-01-01 00:00:00 blood 1729 #> 3458 75.0 1 1893 1893-01-01 00:00:00 bone 1729 #> 3459 73.0 2 1893 1893-01-31 10:00:01 blood 1730 #> 3460 73.0 2 1893 1893-01-31 10:00:01 bone 1730 #> 3461 65.7 3 1893 1893-03-02 20:00:01 blood 1731 #> 3462 65.7 3 1893 1893-03-02 20:00:01 bone 1731 #> 3463 88.1 4 1893 1893-04-02 06:00:00 blood 1732 #> 3464 88.1 4 1893 1893-04-02 06:00:00 bone 1732 #> 3465 84.7 5 1893 1893-05-02 16:00:01 blood 1733 #> 3466 84.7 5 1893 1893-05-02 16:00:01 bone 1733 #> 3467 88.2 6 1893 1893-06-02 02:00:01 blood 1734 #> 3468 88.2 6 1893 1893-06-02 02:00:01 bone 1734 #> 3469 88.8 7 1893 1893-07-02 12:00:00 blood 1735 #> 3470 88.8 7 1893 1893-07-02 12:00:00 bone 1735 #> 3471 129.2 8 1893 1893-08-01 22:00:01 blood 1736 #> 3472 129.2 8 1893 1893-08-01 22:00:01 bone 1736 #> 3473 77.9 9 1893 1893-09-01 08:00:01 blood 1737 #> 3474 77.9 9 1893 1893-09-01 08:00:01 bone 1737 #> 3475 79.7 10 1893 1893-10-01 18:00:00 blood 1738 #> 3476 79.7 10 1893 1893-10-01 18:00:00 bone 1738 #> 3477 75.1 11 1893 1893-11-01 04:00:01 blood 1739 #> 3478 75.1 11 1893 1893-11-01 04:00:01 bone 1739 #> 3479 93.8 12 1893 1893-12-01 14:00:01 blood 1740 #> 3480 93.8 12 1893 1893-12-01 14:00:01 bone 1740 #> 3481 83.2 1 1894 1894-01-01 00:00:00 blood 1741 #> 3482 83.2 1 1894 1894-01-01 00:00:00 bone 1741 #> 3483 84.6 2 1894 1894-01-31 10:00:01 blood 1742 #> 3484 84.6 2 1894 1894-01-31 10:00:01 bone 1742 #> 3485 52.3 3 1894 1894-03-02 20:00:01 blood 1743 #> 3486 52.3 3 1894 1894-03-02 20:00:01 bone 1743 #> 3487 81.6 4 1894 1894-04-02 06:00:00 blood 1744 #> 3488 81.6 4 1894 1894-04-02 06:00:00 bone 1744 #> 3489 101.2 5 1894 1894-05-02 16:00:01 blood 1745 #> 3490 101.2 5 1894 1894-05-02 16:00:01 bone 1745 #> 3491 98.9 6 1894 1894-06-02 02:00:01 blood 1746 #> 3492 98.9 6 1894 1894-06-02 02:00:01 bone 1746 #> 3493 106.0 7 1894 1894-07-02 12:00:00 blood 1747 #> 3494 106.0 7 1894 1894-07-02 12:00:00 bone 1747 #> 3495 70.3 8 1894 1894-08-01 22:00:01 blood 1748 #> 3496 70.3 8 1894 1894-08-01 22:00:01 bone 1748 #> 3497 65.9 9 1894 1894-09-01 08:00:01 blood 1749 #> 3498 65.9 9 1894 1894-09-01 08:00:01 bone 1749 #> 3499 75.5 10 1894 1894-10-01 18:00:00 blood 1750 #> 3500 75.5 10 1894 1894-10-01 18:00:00 bone 1750 #> 3501 56.6 11 1894 1894-11-01 04:00:01 blood 1751 #> 3502 56.6 11 1894 1894-11-01 04:00:01 bone 1751 #> 3503 60.0 12 1894 1894-12-01 14:00:01 blood 1752 #> 3504 60.0 12 1894 1894-12-01 14:00:01 bone 1752 #> 3505 63.3 1 1895 1895-01-01 00:00:00 blood 1753 #> 3506 63.3 1 1895 1895-01-01 00:00:00 bone 1753 #> 3507 67.2 2 1895 1895-01-31 10:00:01 blood 1754 #> 3508 67.2 2 1895 1895-01-31 10:00:01 bone 1754 #> 3509 61.0 3 1895 1895-03-02 20:00:01 blood 1755 #> 3510 61.0 3 1895 1895-03-02 20:00:01 bone 1755 #> 3511 76.9 4 1895 1895-04-02 06:00:00 blood 1756 #> 3512 76.9 4 1895 1895-04-02 06:00:00 bone 1756 #> 3513 67.5 5 1895 1895-05-02 16:00:01 blood 1757 #> 3514 67.5 5 1895 1895-05-02 16:00:01 bone 1757 #> 3515 71.5 6 1895 1895-06-02 02:00:01 blood 1758 #> 3516 71.5 6 1895 1895-06-02 02:00:01 bone 1758 #> 3517 47.8 7 1895 1895-07-02 12:00:00 blood 1759 #> 3518 47.8 7 1895 1895-07-02 12:00:00 bone 1759 #> 3519 68.9 8 1895 1895-08-01 22:00:01 blood 1760 #> 3520 68.9 8 1895 1895-08-01 22:00:01 bone 1760 #> 3521 57.7 9 1895 1895-09-01 08:00:01 blood 1761 #> 3522 57.7 9 1895 1895-09-01 08:00:01 bone 1761 #> 3523 67.9 10 1895 1895-10-01 18:00:00 blood 1762 #> 3524 67.9 10 1895 1895-10-01 18:00:00 bone 1762 #> 3525 47.2 11 1895 1895-11-01 04:00:01 blood 1763 #> 3526 47.2 11 1895 1895-11-01 04:00:01 bone 1763 #> 3527 70.7 12 1895 1895-12-01 14:00:01 blood 1764 #> 3528 70.7 12 1895 1895-12-01 14:00:01 bone 1764 #> 3529 29.0 1 1896 1896-01-01 00:00:00 blood 1765 #> 3530 29.0 1 1896 1896-01-01 00:00:00 bone 1765 #> 3531 57.4 2 1896 1896-01-31 12:00:01 blood 1766 #> 3532 57.4 2 1896 1896-01-31 12:00:01 bone 1766 #> 3533 52.0 3 1896 1896-03-02 00:00:01 blood 1767 #> 3534 52.0 3 1896 1896-03-02 00:00:01 bone 1767 #> 3535 43.8 4 1896 1896-04-01 12:00:00 blood 1768 #> 3536 43.8 4 1896 1896-04-01 12:00:00 bone 1768 #> 3537 27.7 5 1896 1896-05-02 00:00:01 blood 1769 #> 3538 27.7 5 1896 1896-05-02 00:00:01 bone 1769 #> 3539 49.0 6 1896 1896-06-01 12:00:01 blood 1770 #> 3540 49.0 6 1896 1896-06-01 12:00:01 bone 1770 #> 3541 45.0 7 1896 1896-07-02 00:00:00 blood 1771 #> 3542 45.0 7 1896 1896-07-02 00:00:00 bone 1771 #> 3543 27.2 8 1896 1896-08-01 12:00:01 blood 1772 #> 3544 27.2 8 1896 1896-08-01 12:00:01 bone 1772 #> 3545 61.3 9 1896 1896-09-01 00:00:01 blood 1773 #> 3546 61.3 9 1896 1896-09-01 00:00:01 bone 1773 #> 3547 28.4 10 1896 1896-10-01 12:00:00 blood 1774 #> 3548 28.4 10 1896 1896-10-01 12:00:00 bone 1774 #> 3549 38.0 11 1896 1896-11-01 00:00:01 blood 1775 #> 3550 38.0 11 1896 1896-11-01 00:00:01 bone 1775 #> 3551 42.6 12 1896 1896-12-01 12:00:01 blood 1776 #> 3552 42.6 12 1896 1896-12-01 12:00:01 bone 1776 #> 3553 40.6 1 1897 1897-01-01 00:00:00 blood 1777 #> 3554 40.6 1 1897 1897-01-01 00:00:00 bone 1777 #> 3555 29.4 2 1897 1897-01-31 10:00:01 blood 1778 #> 3556 29.4 2 1897 1897-01-31 10:00:01 bone 1778 #> 3557 29.1 3 1897 1897-03-02 20:00:01 blood 1779 #> 3558 29.1 3 1897 1897-03-02 20:00:01 bone 1779 #> 3559 31.0 4 1897 1897-04-02 06:00:00 blood 1780 #> 3560 31.0 4 1897 1897-04-02 06:00:00 bone 1780 #> 3561 20.0 5 1897 1897-05-02 16:00:01 blood 1781 #> 3562 20.0 5 1897 1897-05-02 16:00:01 bone 1781 #> 3563 11.3 6 1897 1897-06-02 02:00:01 blood 1782 #> 3564 11.3 6 1897 1897-06-02 02:00:01 bone 1782 #> 3565 27.6 7 1897 1897-07-02 12:00:00 blood 1783 #> 3566 27.6 7 1897 1897-07-02 12:00:00 bone 1783 #> 3567 21.8 8 1897 1897-08-01 22:00:01 blood 1784 #> 3568 21.8 8 1897 1897-08-01 22:00:01 bone 1784 #> 3569 48.1 9 1897 1897-09-01 08:00:01 blood 1785 #> 3570 48.1 9 1897 1897-09-01 08:00:01 bone 1785 #> 3571 14.3 10 1897 1897-10-01 18:00:00 blood 1786 #> 3572 14.3 10 1897 1897-10-01 18:00:00 bone 1786 #> 3573 8.4 11 1897 1897-11-01 04:00:01 blood 1787 #> 3574 8.4 11 1897 1897-11-01 04:00:01 bone 1787 #> 3575 33.3 12 1897 1897-12-01 14:00:01 blood 1788 #> 3576 33.3 12 1897 1897-12-01 14:00:01 bone 1788 #> 3577 30.2 1 1898 1898-01-01 00:00:00 blood 1789 #> 3578 30.2 1 1898 1898-01-01 00:00:00 bone 1789 #> 3579 36.4 2 1898 1898-01-31 10:00:01 blood 1790 #> 3580 36.4 2 1898 1898-01-31 10:00:01 bone 1790 #> 3581 38.3 3 1898 1898-03-02 20:00:01 blood 1791 #> 3582 38.3 3 1898 1898-03-02 20:00:01 bone 1791 #> 3583 14.5 4 1898 1898-04-02 06:00:00 blood 1792 #> 3584 14.5 4 1898 1898-04-02 06:00:00 bone 1792 #> 3585 25.8 5 1898 1898-05-02 16:00:01 blood 1793 #> 3586 25.8 5 1898 1898-05-02 16:00:01 bone 1793 #> 3587 22.3 6 1898 1898-06-02 02:00:01 blood 1794 #> 3588 22.3 6 1898 1898-06-02 02:00:01 bone 1794 #> 3589 9.0 7 1898 1898-07-02 12:00:00 blood 1795 #> 3590 9.0 7 1898 1898-07-02 12:00:00 bone 1795 #> 3591 31.4 8 1898 1898-08-01 22:00:01 blood 1796 #> 3592 31.4 8 1898 1898-08-01 22:00:01 bone 1796 #> 3593 34.8 9 1898 1898-09-01 08:00:01 blood 1797 #> 3594 34.8 9 1898 1898-09-01 08:00:01 bone 1797 #> 3595 34.4 10 1898 1898-10-01 18:00:00 blood 1798 #> 3596 34.4 10 1898 1898-10-01 18:00:00 bone 1798 #> 3597 30.9 11 1898 1898-11-01 04:00:01 blood 1799 #> 3598 30.9 11 1898 1898-11-01 04:00:01 bone 1799 #> 3599 12.6 12 1898 1898-12-01 14:00:01 blood 1800 #> 3600 12.6 12 1898 1898-12-01 14:00:01 bone 1800 #> 3601 19.5 1 1899 1899-01-01 00:00:00 blood 1801 #> 3602 19.5 1 1899 1899-01-01 00:00:00 bone 1801 #> 3603 9.2 2 1899 1899-01-31 10:00:01 blood 1802 #> 3604 9.2 2 1899 1899-01-31 10:00:01 bone 1802 #> 3605 18.1 3 1899 1899-03-02 20:00:01 blood 1803 #> 3606 18.1 3 1899 1899-03-02 20:00:01 bone 1803 #> 3607 14.2 4 1899 1899-04-02 06:00:00 blood 1804 #> 3608 14.2 4 1899 1899-04-02 06:00:00 bone 1804 #> 3609 7.7 5 1899 1899-05-02 16:00:01 blood 1805 #> 3610 7.7 5 1899 1899-05-02 16:00:01 bone 1805 #> 3611 20.5 6 1899 1899-06-02 02:00:01 blood 1806 #> 3612 20.5 6 1899 1899-06-02 02:00:01 bone 1806 #> 3613 13.5 7 1899 1899-07-02 12:00:00 blood 1807 #> 3614 13.5 7 1899 1899-07-02 12:00:00 bone 1807 #> 3615 2.9 8 1899 1899-08-01 22:00:01 blood 1808 #> 3616 2.9 8 1899 1899-08-01 22:00:01 bone 1808 #> 3617 8.4 9 1899 1899-09-01 08:00:01 blood 1809 #> 3618 8.4 9 1899 1899-09-01 08:00:01 bone 1809 #> 3619 13.0 10 1899 1899-10-01 18:00:00 blood 1810 #> 3620 13.0 10 1899 1899-10-01 18:00:00 bone 1810 #> 3621 7.8 11 1899 1899-11-01 04:00:01 blood 1811 #> 3622 7.8 11 1899 1899-11-01 04:00:01 bone 1811 #> 3623 10.5 12 1899 1899-12-01 14:00:01 blood 1812 #> 3624 10.5 12 1899 1899-12-01 14:00:01 bone 1812 #> 3625 9.4 1 1900 1900-01-01 00:00:00 blood 1813 #> 3626 9.4 1 1900 1900-01-01 00:00:00 bone 1813 #> 3627 13.6 2 1900 1900-01-31 10:00:01 blood 1814 #> 3628 13.6 2 1900 1900-01-31 10:00:01 bone 1814 #> 3629 8.6 3 1900 1900-03-02 20:00:01 blood 1815 #> 3630 8.6 3 1900 1900-03-02 20:00:01 bone 1815 #> 3631 16.0 4 1900 1900-04-02 06:00:00 blood 1816 #> 3632 16.0 4 1900 1900-04-02 06:00:00 bone 1816 #> 3633 15.2 5 1900 1900-05-02 16:00:01 blood 1817 #> 3634 15.2 5 1900 1900-05-02 16:00:01 bone 1817 #> 3635 12.1 6 1900 1900-06-02 02:00:01 blood 1818 #> 3636 12.1 6 1900 1900-06-02 02:00:01 bone 1818 #> 3637 8.3 7 1900 1900-07-02 12:00:00 blood 1819 #> 3638 8.3 7 1900 1900-07-02 12:00:00 bone 1819 #> 3639 4.3 8 1900 1900-08-01 22:00:01 blood 1820 #> 3640 4.3 8 1900 1900-08-01 22:00:01 bone 1820 #> 3641 8.3 9 1900 1900-09-01 08:00:01 blood 1821 #> 3642 8.3 9 1900 1900-09-01 08:00:01 bone 1821 #> 3643 12.9 10 1900 1900-10-01 18:00:00 blood 1822 #> 3644 12.9 10 1900 1900-10-01 18:00:00 bone 1822 #> 3645 4.5 11 1900 1900-11-01 04:00:01 blood 1823 #> 3646 4.5 11 1900 1900-11-01 04:00:01 bone 1823 #> 3647 0.3 12 1900 1900-12-01 14:00:01 blood 1824 #> 3648 0.3 12 1900 1900-12-01 14:00:01 bone 1824 #> 3649 0.2 1 1901 1901-01-01 00:00:00 blood 1825 #> 3650 0.2 1 1901 1901-01-01 00:00:00 bone 1825 #> 3651 2.4 2 1901 1901-01-31 10:00:01 blood 1826 #> 3652 2.4 2 1901 1901-01-31 10:00:01 bone 1826 #> 3653 4.5 3 1901 1901-03-02 20:00:01 blood 1827 #> 3654 4.5 3 1901 1901-03-02 20:00:01 bone 1827 #> 3655 0.0 4 1901 1901-04-02 06:00:00 blood 1828 #> 3656 0.0 4 1901 1901-04-02 06:00:00 bone 1828 #> 3657 10.2 5 1901 1901-05-02 16:00:01 blood 1829 #> 3658 10.2 5 1901 1901-05-02 16:00:01 bone 1829 #> 3659 5.8 6 1901 1901-06-02 02:00:01 blood 1830 #> 3660 5.8 6 1901 1901-06-02 02:00:01 bone 1830 #> 3661 0.7 7 1901 1901-07-02 12:00:00 blood 1831 #> 3662 0.7 7 1901 1901-07-02 12:00:00 bone 1831 #> 3663 1.0 8 1901 1901-08-01 22:00:01 blood 1832 #> 3664 1.0 8 1901 1901-08-01 22:00:01 bone 1832 #> 3665 0.6 9 1901 1901-09-01 08:00:01 blood 1833 #> 3666 0.6 9 1901 1901-09-01 08:00:01 bone 1833 #> 3667 3.7 10 1901 1901-10-01 18:00:00 blood 1834 #> 3668 3.7 10 1901 1901-10-01 18:00:00 bone 1834 #> 3669 3.8 11 1901 1901-11-01 04:00:01 blood 1835 #> 3670 3.8 11 1901 1901-11-01 04:00:01 bone 1835 #> 3671 0.0 12 1901 1901-12-01 14:00:01 blood 1836 #> 3672 0.0 12 1901 1901-12-01 14:00:01 bone 1836 #> 3673 5.2 1 1902 1902-01-01 00:00:00 blood 1837 #> 3674 5.2 1 1902 1902-01-01 00:00:00 bone 1837 #> 3675 0.0 2 1902 1902-01-31 10:00:01 blood 1838 #> 3676 0.0 2 1902 1902-01-31 10:00:01 bone 1838 #> 3677 12.4 3 1902 1902-03-02 20:00:01 blood 1839 #> 3678 12.4 3 1902 1902-03-02 20:00:01 bone 1839 #> 3679 0.0 4 1902 1902-04-02 06:00:00 blood 1840 #> 3680 0.0 4 1902 1902-04-02 06:00:00 bone 1840 #> 3681 2.8 5 1902 1902-05-02 16:00:01 blood 1841 #> 3682 2.8 5 1902 1902-05-02 16:00:01 bone 1841 #> 3683 1.4 6 1902 1902-06-02 02:00:01 blood 1842 #> 3684 1.4 6 1902 1902-06-02 02:00:01 bone 1842 #> 3685 0.9 7 1902 1902-07-02 12:00:00 blood 1843 #> 3686 0.9 7 1902 1902-07-02 12:00:00 bone 1843 #> 3687 2.3 8 1902 1902-08-01 22:00:01 blood 1844 #> 3688 2.3 8 1902 1902-08-01 22:00:01 bone 1844 #> 3689 7.6 9 1902 1902-09-01 08:00:01 blood 1845 #> 3690 7.6 9 1902 1902-09-01 08:00:01 bone 1845 #> 3691 16.3 10 1902 1902-10-01 18:00:00 blood 1846 #> 3692 16.3 10 1902 1902-10-01 18:00:00 bone 1846 #> 3693 10.3 11 1902 1902-11-01 04:00:01 blood 1847 #> 3694 10.3 11 1902 1902-11-01 04:00:01 bone 1847 #> 3695 1.1 12 1902 1902-12-01 14:00:01 blood 1848 #> 3696 1.1 12 1902 1902-12-01 14:00:01 bone 1848 #> 3697 8.3 1 1903 1903-01-01 00:00:00 blood 1849 #> 3698 8.3 1 1903 1903-01-01 00:00:00 bone 1849 #> 3699 17.0 2 1903 1903-01-31 10:00:01 blood 1850 #> 3700 17.0 2 1903 1903-01-31 10:00:01 bone 1850 #> 3701 13.5 3 1903 1903-03-02 20:00:01 blood 1851 #> 3702 13.5 3 1903 1903-03-02 20:00:01 bone 1851 #> 3703 26.1 4 1903 1903-04-02 06:00:00 blood 1852 #> 3704 26.1 4 1903 1903-04-02 06:00:00 bone 1852 #> 3705 14.6 5 1903 1903-05-02 16:00:01 blood 1853 #> 3706 14.6 5 1903 1903-05-02 16:00:01 bone 1853 #> 3707 16.3 6 1903 1903-06-02 02:00:01 blood 1854 #> 3708 16.3 6 1903 1903-06-02 02:00:01 bone 1854 #> 3709 27.9 7 1903 1903-07-02 12:00:00 blood 1855 #> 3710 27.9 7 1903 1903-07-02 12:00:00 bone 1855 #> 3711 28.8 8 1903 1903-08-01 22:00:01 blood 1856 #> 3712 28.8 8 1903 1903-08-01 22:00:01 bone 1856 #> 3713 11.1 9 1903 1903-09-01 08:00:01 blood 1857 #> 3714 11.1 9 1903 1903-09-01 08:00:01 bone 1857 #> 3715 38.9 10 1903 1903-10-01 18:00:00 blood 1858 #> 3716 38.9 10 1903 1903-10-01 18:00:00 bone 1858 #> 3717 44.5 11 1903 1903-11-01 04:00:01 blood 1859 #> 3718 44.5 11 1903 1903-11-01 04:00:01 bone 1859 #> 3719 45.6 12 1903 1903-12-01 14:00:01 blood 1860 #> 3720 45.6 12 1903 1903-12-01 14:00:01 bone 1860 #> 3721 31.6 1 1904 1904-01-01 00:00:00 blood 1861 #> 3722 31.6 1 1904 1904-01-01 00:00:00 bone 1861 #> 3723 24.5 2 1904 1904-01-31 12:00:01 blood 1862 #> 3724 24.5 2 1904 1904-01-31 12:00:01 bone 1862 #> 3725 37.2 3 1904 1904-03-02 00:00:01 blood 1863 #> 3726 37.2 3 1904 1904-03-02 00:00:01 bone 1863 #> 3727 43.0 4 1904 1904-04-01 12:00:00 blood 1864 #> 3728 43.0 4 1904 1904-04-01 12:00:00 bone 1864 #> 3729 39.5 5 1904 1904-05-02 00:00:01 blood 1865 #> 3730 39.5 5 1904 1904-05-02 00:00:01 bone 1865 #> 3731 41.9 6 1904 1904-06-01 12:00:01 blood 1866 #> 3732 41.9 6 1904 1904-06-01 12:00:01 bone 1866 #> 3733 50.6 7 1904 1904-07-02 00:00:00 blood 1867 #> 3734 50.6 7 1904 1904-07-02 00:00:00 bone 1867 #> 3735 58.2 8 1904 1904-08-01 12:00:01 blood 1868 #> 3736 58.2 8 1904 1904-08-01 12:00:01 bone 1868 #> 3737 30.1 9 1904 1904-09-01 00:00:01 blood 1869 #> 3738 30.1 9 1904 1904-09-01 00:00:01 bone 1869 #> 3739 54.2 10 1904 1904-10-01 12:00:00 blood 1870 #> 3740 54.2 10 1904 1904-10-01 12:00:00 bone 1870 #> 3741 38.0 11 1904 1904-11-01 00:00:01 blood 1871 #> 3742 38.0 11 1904 1904-11-01 00:00:01 bone 1871 #> 3743 54.6 12 1904 1904-12-01 12:00:01 blood 1872 #> 3744 54.6 12 1904 1904-12-01 12:00:01 bone 1872 #> 3745 54.8 1 1905 1905-01-01 00:00:00 blood 1873 #> 3746 54.8 1 1905 1905-01-01 00:00:00 bone 1873 #> 3747 85.8 2 1905 1905-01-31 10:00:01 blood 1874 #> 3748 85.8 2 1905 1905-01-31 10:00:01 bone 1874 #> 3749 56.5 3 1905 1905-03-02 20:00:01 blood 1875 #> 3750 56.5 3 1905 1905-03-02 20:00:01 bone 1875 #> 3751 39.3 4 1905 1905-04-02 06:00:00 blood 1876 #> 3752 39.3 4 1905 1905-04-02 06:00:00 bone 1876 #> 3753 48.0 5 1905 1905-05-02 16:00:01 blood 1877 #> 3754 48.0 5 1905 1905-05-02 16:00:01 bone 1877 #> 3755 49.0 6 1905 1905-06-02 02:00:01 blood 1878 #> 3756 49.0 6 1905 1905-06-02 02:00:01 bone 1878 #> 3757 73.0 7 1905 1905-07-02 12:00:00 blood 1879 #> 3758 73.0 7 1905 1905-07-02 12:00:00 bone 1879 #> 3759 58.8 8 1905 1905-08-01 22:00:01 blood 1880 #> 3760 58.8 8 1905 1905-08-01 22:00:01 bone 1880 #> 3761 55.0 9 1905 1905-09-01 08:00:01 blood 1881 #> 3762 55.0 9 1905 1905-09-01 08:00:01 bone 1881 #> 3763 78.7 10 1905 1905-10-01 18:00:00 blood 1882 #> 3764 78.7 10 1905 1905-10-01 18:00:00 bone 1882 #> 3765 107.2 11 1905 1905-11-01 04:00:01 blood 1883 #> 3766 107.2 11 1905 1905-11-01 04:00:01 bone 1883 #> 3767 55.5 12 1905 1905-12-01 14:00:01 blood 1884 #> 3768 55.5 12 1905 1905-12-01 14:00:01 bone 1884 #> 3769 45.5 1 1906 1906-01-01 00:00:00 blood 1885 #> 3770 45.5 1 1906 1906-01-01 00:00:00 bone 1885 #> 3771 31.3 2 1906 1906-01-31 10:00:01 blood 1886 #> 3772 31.3 2 1906 1906-01-31 10:00:01 bone 1886 #> 3773 64.5 3 1906 1906-03-02 20:00:01 blood 1887 #> 3774 64.5 3 1906 1906-03-02 20:00:01 bone 1887 #> 3775 55.3 4 1906 1906-04-02 06:00:00 blood 1888 #> 3776 55.3 4 1906 1906-04-02 06:00:00 bone 1888 #> 3777 57.7 5 1906 1906-05-02 16:00:01 blood 1889 #> 3778 57.7 5 1906 1906-05-02 16:00:01 bone 1889 #> 3779 63.2 6 1906 1906-06-02 02:00:01 blood 1890 #> 3780 63.2 6 1906 1906-06-02 02:00:01 bone 1890 #> 3781 103.6 7 1906 1906-07-02 12:00:00 blood 1891 #> 3782 103.6 7 1906 1906-07-02 12:00:00 bone 1891 #> 3783 47.7 8 1906 1906-08-01 22:00:01 blood 1892 #> 3784 47.7 8 1906 1906-08-01 22:00:01 bone 1892 #> 3785 56.1 9 1906 1906-09-01 08:00:01 blood 1893 #> 3786 56.1 9 1906 1906-09-01 08:00:01 bone 1893 #> 3787 17.8 10 1906 1906-10-01 18:00:00 blood 1894 #> 3788 17.8 10 1906 1906-10-01 18:00:00 bone 1894 #> 3789 38.9 11 1906 1906-11-01 04:00:01 blood 1895 #> 3790 38.9 11 1906 1906-11-01 04:00:01 bone 1895 #> 3791 64.7 12 1906 1906-12-01 14:00:01 blood 1896 #> 3792 64.7 12 1906 1906-12-01 14:00:01 bone 1896 #> 3793 76.4 1 1907 1907-01-01 00:00:00 blood 1897 #> 3794 76.4 1 1907 1907-01-01 00:00:00 bone 1897 #> 3795 108.2 2 1907 1907-01-31 10:00:01 blood 1898 #> 3796 108.2 2 1907 1907-01-31 10:00:01 bone 1898 #> 3797 60.7 3 1907 1907-03-02 20:00:01 blood 1899 #> 3798 60.7 3 1907 1907-03-02 20:00:01 bone 1899 #> 3799 52.6 4 1907 1907-04-02 06:00:00 blood 1900 #> 3800 52.6 4 1907 1907-04-02 06:00:00 bone 1900 #> 3801 42.9 5 1907 1907-05-02 16:00:01 blood 1901 #> 3802 42.9 5 1907 1907-05-02 16:00:01 bone 1901 #> 3803 40.4 6 1907 1907-06-02 02:00:01 blood 1902 #> 3804 40.4 6 1907 1907-06-02 02:00:01 bone 1902 #> 3805 49.7 7 1907 1907-07-02 12:00:00 blood 1903 #> 3806 49.7 7 1907 1907-07-02 12:00:00 bone 1903 #> 3807 54.3 8 1907 1907-08-01 22:00:01 blood 1904 #> 3808 54.3 8 1907 1907-08-01 22:00:01 bone 1904 #> 3809 85.0 9 1907 1907-09-01 08:00:01 blood 1905 #> 3810 85.0 9 1907 1907-09-01 08:00:01 bone 1905 #> 3811 65.4 10 1907 1907-10-01 18:00:00 blood 1906 #> 3812 65.4 10 1907 1907-10-01 18:00:00 bone 1906 #> 3813 61.5 11 1907 1907-11-01 04:00:01 blood 1907 #> 3814 61.5 11 1907 1907-11-01 04:00:01 bone 1907 #> 3815 47.3 12 1907 1907-12-01 14:00:01 blood 1908 #> 3816 47.3 12 1907 1907-12-01 14:00:01 bone 1908 #> 3817 39.2 1 1908 1908-01-01 00:00:00 blood 1909 #> 3818 39.2 1 1908 1908-01-01 00:00:00 bone 1909 #> 3819 33.9 2 1908 1908-01-31 12:00:01 blood 1910 #> 3820 33.9 2 1908 1908-01-31 12:00:01 bone 1910 #> 3821 28.7 3 1908 1908-03-02 00:00:01 blood 1911 #> 3822 28.7 3 1908 1908-03-02 00:00:01 bone 1911 #> 3823 57.6 4 1908 1908-04-01 12:00:00 blood 1912 #> 3824 57.6 4 1908 1908-04-01 12:00:00 bone 1912 #> 3825 40.8 5 1908 1908-05-02 00:00:01 blood 1913 #> 3826 40.8 5 1908 1908-05-02 00:00:01 bone 1913 #> 3827 48.1 6 1908 1908-06-01 12:00:01 blood 1914 #> 3828 48.1 6 1908 1908-06-01 12:00:01 bone 1914 #> 3829 39.5 7 1908 1908-07-02 00:00:00 blood 1915 #> 3830 39.5 7 1908 1908-07-02 00:00:00 bone 1915 #> 3831 90.5 8 1908 1908-08-01 12:00:01 blood 1916 #> 3832 90.5 8 1908 1908-08-01 12:00:01 bone 1916 #> 3833 86.9 9 1908 1908-09-01 00:00:01 blood 1917 #> 3834 86.9 9 1908 1908-09-01 00:00:01 bone 1917 #> 3835 32.3 10 1908 1908-10-01 12:00:00 blood 1918 #> 3836 32.3 10 1908 1908-10-01 12:00:00 bone 1918 #> 3837 45.5 11 1908 1908-11-01 00:00:01 blood 1919 #> 3838 45.5 11 1908 1908-11-01 00:00:01 bone 1919 #> 3839 39.5 12 1908 1908-12-01 12:00:01 blood 1920 #> 3840 39.5 12 1908 1908-12-01 12:00:01 bone 1920 #> 3841 56.7 1 1909 1909-01-01 00:00:00 blood 1921 #> 3842 56.7 1 1909 1909-01-01 00:00:00 bone 1921 #> 3843 46.6 2 1909 1909-01-31 10:00:01 blood 1922 #> 3844 46.6 2 1909 1909-01-31 10:00:01 bone 1922 #> 3845 66.3 3 1909 1909-03-02 20:00:01 blood 1923 #> 3846 66.3 3 1909 1909-03-02 20:00:01 bone 1923 #> 3847 32.3 4 1909 1909-04-02 06:00:00 blood 1924 #> 3848 32.3 4 1909 1909-04-02 06:00:00 bone 1924 #> 3849 36.0 5 1909 1909-05-02 16:00:01 blood 1925 #> 3850 36.0 5 1909 1909-05-02 16:00:01 bone 1925 #> 3851 22.6 6 1909 1909-06-02 02:00:01 blood 1926 #> 3852 22.6 6 1909 1909-06-02 02:00:01 bone 1926 #> 3853 35.8 7 1909 1909-07-02 12:00:00 blood 1927 #> 3854 35.8 7 1909 1909-07-02 12:00:00 bone 1927 #> 3855 23.1 8 1909 1909-08-01 22:00:01 blood 1928 #> 3856 23.1 8 1909 1909-08-01 22:00:01 bone 1928 #> 3857 38.8 9 1909 1909-09-01 08:00:01 blood 1929 #> 3858 38.8 9 1909 1909-09-01 08:00:01 bone 1929 #> 3859 58.4 10 1909 1909-10-01 18:00:00 blood 1930 #> 3860 58.4 10 1909 1909-10-01 18:00:00 bone 1930 #> 3861 55.8 11 1909 1909-11-01 04:00:01 blood 1931 #> 3862 55.8 11 1909 1909-11-01 04:00:01 bone 1931 #> 3863 54.2 12 1909 1909-12-01 14:00:01 blood 1932 #> 3864 54.2 12 1909 1909-12-01 14:00:01 bone 1932 #> 3865 26.4 1 1910 1910-01-01 00:00:00 blood 1933 #> 3866 26.4 1 1910 1910-01-01 00:00:00 bone 1933 #> 3867 31.5 2 1910 1910-01-31 10:00:01 blood 1934 #> 3868 31.5 2 1910 1910-01-31 10:00:01 bone 1934 #> 3869 21.4 3 1910 1910-03-02 20:00:01 blood 1935 #> 3870 21.4 3 1910 1910-03-02 20:00:01 bone 1935 #> 3871 8.4 4 1910 1910-04-02 06:00:00 blood 1936 #> 3872 8.4 4 1910 1910-04-02 06:00:00 bone 1936 #> 3873 22.2 5 1910 1910-05-02 16:00:01 blood 1937 #> 3874 22.2 5 1910 1910-05-02 16:00:01 bone 1937 #> 3875 12.3 6 1910 1910-06-02 02:00:01 blood 1938 #> 3876 12.3 6 1910 1910-06-02 02:00:01 bone 1938 #> 3877 14.1 7 1910 1910-07-02 12:00:00 blood 1939 #> 3878 14.1 7 1910 1910-07-02 12:00:00 bone 1939 #> 3879 11.5 8 1910 1910-08-01 22:00:01 blood 1940 #> 3880 11.5 8 1910 1910-08-01 22:00:01 bone 1940 #> 3881 26.2 9 1910 1910-09-01 08:00:01 blood 1941 #> 3882 26.2 9 1910 1910-09-01 08:00:01 bone 1941 #> 3883 38.3 10 1910 1910-10-01 18:00:00 blood 1942 #> 3884 38.3 10 1910 1910-10-01 18:00:00 bone 1942 #> 3885 4.9 11 1910 1910-11-01 04:00:01 blood 1943 #> 3886 4.9 11 1910 1910-11-01 04:00:01 bone 1943 #> 3887 5.8 12 1910 1910-12-01 14:00:01 blood 1944 #> 3888 5.8 12 1910 1910-12-01 14:00:01 bone 1944 #> 3889 3.4 1 1911 1911-01-01 00:00:00 blood 1945 #> 3890 3.4 1 1911 1911-01-01 00:00:00 bone 1945 #> 3891 9.0 2 1911 1911-01-31 10:00:01 blood 1946 #> 3892 9.0 2 1911 1911-01-31 10:00:01 bone 1946 #> 3893 7.8 3 1911 1911-03-02 20:00:01 blood 1947 #> 3894 7.8 3 1911 1911-03-02 20:00:01 bone 1947 #> 3895 16.5 4 1911 1911-04-02 06:00:00 blood 1948 #> 3896 16.5 4 1911 1911-04-02 06:00:00 bone 1948 #> 3897 9.0 5 1911 1911-05-02 16:00:01 blood 1949 #> 3898 9.0 5 1911 1911-05-02 16:00:01 bone 1949 #> 3899 2.2 6 1911 1911-06-02 02:00:01 blood 1950 #> 3900 2.2 6 1911 1911-06-02 02:00:01 bone 1950 #> 3901 3.5 7 1911 1911-07-02 12:00:00 blood 1951 #> 3902 3.5 7 1911 1911-07-02 12:00:00 bone 1951 #> 3903 4.0 8 1911 1911-08-01 22:00:01 blood 1952 #> 3904 4.0 8 1911 1911-08-01 22:00:01 bone 1952 #> 3905 4.0 9 1911 1911-09-01 08:00:01 blood 1953 #> 3906 4.0 9 1911 1911-09-01 08:00:01 bone 1953 #> 3907 2.6 10 1911 1911-10-01 18:00:00 blood 1954 #> 3908 2.6 10 1911 1911-10-01 18:00:00 bone 1954 #> 3909 4.2 11 1911 1911-11-01 04:00:01 blood 1955 #> 3910 4.2 11 1911 1911-11-01 04:00:01 bone 1955 #> 3911 2.2 12 1911 1911-12-01 14:00:01 blood 1956 #> 3912 2.2 12 1911 1911-12-01 14:00:01 bone 1956 #> 3913 0.3 1 1912 1912-01-01 00:00:00 blood 1957 #> 3914 0.3 1 1912 1912-01-01 00:00:00 bone 1957 #> 3915 0.0 2 1912 1912-01-31 12:00:01 blood 1958 #> 3916 0.0 2 1912 1912-01-31 12:00:01 bone 1958 #> 3917 4.9 3 1912 1912-03-02 00:00:01 blood 1959 #> 3918 4.9 3 1912 1912-03-02 00:00:01 bone 1959 #> 3919 4.5 4 1912 1912-04-01 12:00:00 blood 1960 #> 3920 4.5 4 1912 1912-04-01 12:00:00 bone 1960 #> 3921 4.4 5 1912 1912-05-02 00:00:01 blood 1961 #> 3922 4.4 5 1912 1912-05-02 00:00:01 bone 1961 #> 3923 4.1 6 1912 1912-06-01 12:00:01 blood 1962 #> 3924 4.1 6 1912 1912-06-01 12:00:01 bone 1962 #> 3925 3.0 7 1912 1912-07-02 00:00:00 blood 1963 #> 3926 3.0 7 1912 1912-07-02 00:00:00 bone 1963 #> 3927 0.3 8 1912 1912-08-01 12:00:01 blood 1964 #> 3928 0.3 8 1912 1912-08-01 12:00:01 bone 1964 #> 3929 9.5 9 1912 1912-09-01 00:00:01 blood 1965 #> 3930 9.5 9 1912 1912-09-01 00:00:01 bone 1965 #> 3931 4.6 10 1912 1912-10-01 12:00:00 blood 1966 #> 3932 4.6 10 1912 1912-10-01 12:00:00 bone 1966 #> 3933 1.1 11 1912 1912-11-01 00:00:01 blood 1967 #> 3934 1.1 11 1912 1912-11-01 00:00:01 bone 1967 #> 3935 6.4 12 1912 1912-12-01 12:00:01 blood 1968 #> 3936 6.4 12 1912 1912-12-01 12:00:01 bone 1968 #> 3937 2.3 1 1913 1913-01-01 00:00:00 blood 1969 #> 3938 2.3 1 1913 1913-01-01 00:00:00 bone 1969 #> 3939 2.9 2 1913 1913-01-31 10:00:01 blood 1970 #> 3940 2.9 2 1913 1913-01-31 10:00:01 bone 1970 #> 3941 0.5 3 1913 1913-03-02 20:00:01 blood 1971 #> 3942 0.5 3 1913 1913-03-02 20:00:01 bone 1971 #> 3943 0.9 4 1913 1913-04-02 06:00:00 blood 1972 #> 3944 0.9 4 1913 1913-04-02 06:00:00 bone 1972 #> 3945 0.0 5 1913 1913-05-02 16:00:01 blood 1973 #> 3946 0.0 5 1913 1913-05-02 16:00:01 bone 1973 #> 3947 0.0 6 1913 1913-06-02 02:00:01 blood 1974 #> 3948 0.0 6 1913 1913-06-02 02:00:01 bone 1974 #> 3949 1.7 7 1913 1913-07-02 12:00:00 blood 1975 #> 3950 1.7 7 1913 1913-07-02 12:00:00 bone 1975 #> 3951 0.2 8 1913 1913-08-01 22:00:01 blood 1976 #> 3952 0.2 8 1913 1913-08-01 22:00:01 bone 1976 #> 3953 1.2 9 1913 1913-09-01 08:00:01 blood 1977 #> 3954 1.2 9 1913 1913-09-01 08:00:01 bone 1977 #> 3955 3.1 10 1913 1913-10-01 18:00:00 blood 1978 #> 3956 3.1 10 1913 1913-10-01 18:00:00 bone 1978 #> 3957 0.7 11 1913 1913-11-01 04:00:01 blood 1979 #> 3958 0.7 11 1913 1913-11-01 04:00:01 bone 1979 #> 3959 3.8 12 1913 1913-12-01 14:00:01 blood 1980 #> 3960 3.8 12 1913 1913-12-01 14:00:01 bone 1980 #> 3961 2.8 1 1914 1914-01-01 00:00:00 blood 1981 #> 3962 2.8 1 1914 1914-01-01 00:00:00 bone 1981 #> 3963 2.6 2 1914 1914-01-31 10:00:01 blood 1982 #> 3964 2.6 2 1914 1914-01-31 10:00:01 bone 1982 #> 3965 3.1 3 1914 1914-03-02 20:00:01 blood 1983 #> 3966 3.1 3 1914 1914-03-02 20:00:01 bone 1983 #> 3967 17.3 4 1914 1914-04-02 06:00:00 blood 1984 #> 3968 17.3 4 1914 1914-04-02 06:00:00 bone 1984 #> 3969 5.2 5 1914 1914-05-02 16:00:01 blood 1985 #> 3970 5.2 5 1914 1914-05-02 16:00:01 bone 1985 #> 3971 11.4 6 1914 1914-06-02 02:00:01 blood 1986 #> 3972 11.4 6 1914 1914-06-02 02:00:01 bone 1986 #> 3973 5.4 7 1914 1914-07-02 12:00:00 blood 1987 #> 3974 5.4 7 1914 1914-07-02 12:00:00 bone 1987 #> 3975 7.7 8 1914 1914-08-01 22:00:01 blood 1988 #> 3976 7.7 8 1914 1914-08-01 22:00:01 bone 1988 #> 3977 12.7 9 1914 1914-09-01 08:00:01 blood 1989 #> 3978 12.7 9 1914 1914-09-01 08:00:01 bone 1989 #> 3979 8.2 10 1914 1914-10-01 18:00:00 blood 1990 #> 3980 8.2 10 1914 1914-10-01 18:00:00 bone 1990 #> 3981 16.4 11 1914 1914-11-01 04:00:01 blood 1991 #> 3982 16.4 11 1914 1914-11-01 04:00:01 bone 1991 #> 3983 22.3 12 1914 1914-12-01 14:00:01 blood 1992 #> 3984 22.3 12 1914 1914-12-01 14:00:01 bone 1992 #> 3985 23.0 1 1915 1915-01-01 00:00:00 blood 1993 #> 3986 23.0 1 1915 1915-01-01 00:00:00 bone 1993 #> 3987 42.3 2 1915 1915-01-31 10:00:01 blood 1994 #> 3988 42.3 2 1915 1915-01-31 10:00:01 bone 1994 #> 3989 38.8 3 1915 1915-03-02 20:00:01 blood 1995 #> 3990 38.8 3 1915 1915-03-02 20:00:01 bone 1995 #> 3991 41.3 4 1915 1915-04-02 06:00:00 blood 1996 #> 3992 41.3 4 1915 1915-04-02 06:00:00 bone 1996 #> 3993 33.0 5 1915 1915-05-02 16:00:01 blood 1997 #> 3994 33.0 5 1915 1915-05-02 16:00:01 bone 1997 #> 3995 68.8 6 1915 1915-06-02 02:00:01 blood 1998 #> 3996 68.8 6 1915 1915-06-02 02:00:01 bone 1998 #> 3997 71.6 7 1915 1915-07-02 12:00:00 blood 1999 #> 3998 71.6 7 1915 1915-07-02 12:00:00 bone 1999 #> 3999 69.6 8 1915 1915-08-01 22:00:01 blood 2000 #> 4000 69.6 8 1915 1915-08-01 22:00:01 bone 2000 #> 4001 49.5 9 1915 1915-09-01 08:00:01 blood 2001 #> 4002 49.5 9 1915 1915-09-01 08:00:01 bone 2001 #> 4003 53.5 10 1915 1915-10-01 18:00:00 blood 2002 #> 4004 53.5 10 1915 1915-10-01 18:00:00 bone 2002 #> 4005 42.5 11 1915 1915-11-01 04:00:01 blood 2003 #> 4006 42.5 11 1915 1915-11-01 04:00:01 bone 2003 #> 4007 34.5 12 1915 1915-12-01 14:00:01 blood 2004 #> 4008 34.5 12 1915 1915-12-01 14:00:01 bone 2004 #> 4009 45.3 1 1916 1916-01-01 00:00:00 blood 2005 #> 4010 45.3 1 1916 1916-01-01 00:00:00 bone 2005 #> 4011 55.4 2 1916 1916-01-31 12:00:01 blood 2006 #> 4012 55.4 2 1916 1916-01-31 12:00:01 bone 2006 #> 4013 67.0 3 1916 1916-03-02 00:00:01 blood 2007 #> 4014 67.0 3 1916 1916-03-02 00:00:01 bone 2007 #> 4015 71.8 4 1916 1916-04-01 12:00:00 blood 2008 #> 4016 71.8 4 1916 1916-04-01 12:00:00 bone 2008 #> 4017 74.5 5 1916 1916-05-02 00:00:01 blood 2009 #> 4018 74.5 5 1916 1916-05-02 00:00:01 bone 2009 #> 4019 67.7 6 1916 1916-06-01 12:00:01 blood 2010 #> 4020 67.7 6 1916 1916-06-01 12:00:01 bone 2010 #> 4021 53.5 7 1916 1916-07-02 00:00:00 blood 2011 #> 4022 53.5 7 1916 1916-07-02 00:00:00 bone 2011 #> 4023 35.2 8 1916 1916-08-01 12:00:01 blood 2012 #> 4024 35.2 8 1916 1916-08-01 12:00:01 bone 2012 #> 4025 45.1 9 1916 1916-09-01 00:00:01 blood 2013 #> 4026 45.1 9 1916 1916-09-01 00:00:01 bone 2013 #> 4027 50.7 10 1916 1916-10-01 12:00:00 blood 2014 #> 4028 50.7 10 1916 1916-10-01 12:00:00 bone 2014 #> 4029 65.6 11 1916 1916-11-01 00:00:01 blood 2015 #> 4030 65.6 11 1916 1916-11-01 00:00:01 bone 2015 #> 4031 53.0 12 1916 1916-12-01 12:00:01 blood 2016 #> 4032 53.0 12 1916 1916-12-01 12:00:01 bone 2016 #> 4033 74.7 1 1917 1917-01-01 00:00:00 blood 2017 #> 4034 74.7 1 1917 1917-01-01 00:00:00 bone 2017 #> 4035 71.9 2 1917 1917-01-31 10:00:01 blood 2018 #> 4036 71.9 2 1917 1917-01-31 10:00:01 bone 2018 #> 4037 94.8 3 1917 1917-03-02 20:00:01 blood 2019 #> 4038 94.8 3 1917 1917-03-02 20:00:01 bone 2019 #> 4039 74.7 4 1917 1917-04-02 06:00:00 blood 2020 #> 4040 74.7 4 1917 1917-04-02 06:00:00 bone 2020 #> 4041 114.1 5 1917 1917-05-02 16:00:01 blood 2021 #> 4042 114.1 5 1917 1917-05-02 16:00:01 bone 2021 #> 4043 114.9 6 1917 1917-06-02 02:00:01 blood 2022 #> 4044 114.9 6 1917 1917-06-02 02:00:01 bone 2022 #> 4045 119.8 7 1917 1917-07-02 12:00:00 blood 2023 #> 4046 119.8 7 1917 1917-07-02 12:00:00 bone 2023 #> 4047 154.5 8 1917 1917-08-01 22:00:01 blood 2024 #> 4048 154.5 8 1917 1917-08-01 22:00:01 bone 2024 #> 4049 129.4 9 1917 1917-09-01 08:00:01 blood 2025 #> 4050 129.4 9 1917 1917-09-01 08:00:01 bone 2025 #> 4051 72.2 10 1917 1917-10-01 18:00:00 blood 2026 #> 4052 72.2 10 1917 1917-10-01 18:00:00 bone 2026 #> 4053 96.4 11 1917 1917-11-01 04:00:01 blood 2027 #> 4054 96.4 11 1917 1917-11-01 04:00:01 bone 2027 #> 4055 129.3 12 1917 1917-12-01 14:00:01 blood 2028 #> 4056 129.3 12 1917 1917-12-01 14:00:01 bone 2028 #> 4057 96.0 1 1918 1918-01-01 00:00:00 blood 2029 #> 4058 96.0 1 1918 1918-01-01 00:00:00 bone 2029 #> 4059 65.3 2 1918 1918-01-31 10:00:01 blood 2030 #> 4060 65.3 2 1918 1918-01-31 10:00:01 bone 2030 #> 4061 72.2 3 1918 1918-03-02 20:00:01 blood 2031 #> 4062 72.2 3 1918 1918-03-02 20:00:01 bone 2031 #> 4063 80.5 4 1918 1918-04-02 06:00:00 blood 2032 #> 4064 80.5 4 1918 1918-04-02 06:00:00 bone 2032 #> 4065 76.7 5 1918 1918-05-02 16:00:01 blood 2033 #> 4066 76.7 5 1918 1918-05-02 16:00:01 bone 2033 #> 4067 59.4 6 1918 1918-06-02 02:00:01 blood 2034 #> 4068 59.4 6 1918 1918-06-02 02:00:01 bone 2034 #> 4069 107.6 7 1918 1918-07-02 12:00:00 blood 2035 #> 4070 107.6 7 1918 1918-07-02 12:00:00 bone 2035 #> 4071 101.7 8 1918 1918-08-01 22:00:01 blood 2036 #> 4072 101.7 8 1918 1918-08-01 22:00:01 bone 2036 #> 4073 79.9 9 1918 1918-09-01 08:00:01 blood 2037 #> 4074 79.9 9 1918 1918-09-01 08:00:01 bone 2037 #> 4075 85.0 10 1918 1918-10-01 18:00:00 blood 2038 #> 4076 85.0 10 1918 1918-10-01 18:00:00 bone 2038 #> 4077 83.4 11 1918 1918-11-01 04:00:01 blood 2039 #> 4078 83.4 11 1918 1918-11-01 04:00:01 bone 2039 #> 4079 59.2 12 1918 1918-12-01 14:00:01 blood 2040 #> 4080 59.2 12 1918 1918-12-01 14:00:01 bone 2040 #> 4081 48.1 1 1919 1919-01-01 00:00:00 blood 2041 #> 4082 48.1 1 1919 1919-01-01 00:00:00 bone 2041 #> 4083 79.5 2 1919 1919-01-31 10:00:01 blood 2042 #> 4084 79.5 2 1919 1919-01-31 10:00:01 bone 2042 #> 4085 66.5 3 1919 1919-03-02 20:00:01 blood 2043 #> 4086 66.5 3 1919 1919-03-02 20:00:01 bone 2043 #> 4087 51.8 4 1919 1919-04-02 06:00:00 blood 2044 #> 4088 51.8 4 1919 1919-04-02 06:00:00 bone 2044 #> 4089 88.1 5 1919 1919-05-02 16:00:01 blood 2045 #> 4090 88.1 5 1919 1919-05-02 16:00:01 bone 2045 #> 4091 111.2 6 1919 1919-06-02 02:00:01 blood 2046 #> 4092 111.2 6 1919 1919-06-02 02:00:01 bone 2046 #> 4093 64.7 7 1919 1919-07-02 12:00:00 blood 2047 #> 4094 64.7 7 1919 1919-07-02 12:00:00 bone 2047 #> 4095 69.0 8 1919 1919-08-01 22:00:01 blood 2048 #> 4096 69.0 8 1919 1919-08-01 22:00:01 bone 2048 #> 4097 54.7 9 1919 1919-09-01 08:00:01 blood 2049 #> 4098 54.7 9 1919 1919-09-01 08:00:01 bone 2049 #> 4099 52.8 10 1919 1919-10-01 18:00:00 blood 2050 #> 4100 52.8 10 1919 1919-10-01 18:00:00 bone 2050 #> 4101 42.0 11 1919 1919-11-01 04:00:01 blood 2051 #> 4102 42.0 11 1919 1919-11-01 04:00:01 bone 2051 #> 4103 34.9 12 1919 1919-12-01 14:00:01 blood 2052 #> 4104 34.9 12 1919 1919-12-01 14:00:01 bone 2052 #> 4105 51.1 1 1920 1920-01-01 00:00:00 blood 2053 #> 4106 51.1 1 1920 1920-01-01 00:00:00 bone 2053 #> 4107 53.9 2 1920 1920-01-31 12:00:01 blood 2054 #> 4108 53.9 2 1920 1920-01-31 12:00:01 bone 2054 #> 4109 70.2 3 1920 1920-03-02 00:00:01 blood 2055 #> 4110 70.2 3 1920 1920-03-02 00:00:01 bone 2055 #> 4111 14.8 4 1920 1920-04-01 12:00:00 blood 2056 #> 4112 14.8 4 1920 1920-04-01 12:00:00 bone 2056 #> 4113 33.3 5 1920 1920-05-02 00:00:01 blood 2057 #> 4114 33.3 5 1920 1920-05-02 00:00:01 bone 2057 #> 4115 38.7 6 1920 1920-06-01 12:00:01 blood 2058 #> 4116 38.7 6 1920 1920-06-01 12:00:01 bone 2058 #> 4117 27.5 7 1920 1920-07-02 00:00:00 blood 2059 #> 4118 27.5 7 1920 1920-07-02 00:00:00 bone 2059 #> 4119 19.2 8 1920 1920-08-01 12:00:01 blood 2060 #> 4120 19.2 8 1920 1920-08-01 12:00:01 bone 2060 #> 4121 36.3 9 1920 1920-09-01 00:00:01 blood 2061 #> 4122 36.3 9 1920 1920-09-01 00:00:01 bone 2061 #> 4123 49.6 10 1920 1920-10-01 12:00:00 blood 2062 #> 4124 49.6 10 1920 1920-10-01 12:00:00 bone 2062 #> 4125 27.2 11 1920 1920-11-01 00:00:01 blood 2063 #> 4126 27.2 11 1920 1920-11-01 00:00:01 bone 2063 #> 4127 29.9 12 1920 1920-12-01 12:00:01 blood 2064 #> 4128 29.9 12 1920 1920-12-01 12:00:01 bone 2064 #> 4129 31.5 1 1921 1921-01-01 00:00:00 blood 2065 #> 4130 31.5 1 1921 1921-01-01 00:00:00 bone 2065 #> 4131 28.3 2 1921 1921-01-31 10:00:01 blood 2066 #> 4132 28.3 2 1921 1921-01-31 10:00:01 bone 2066 #> 4133 26.7 3 1921 1921-03-02 20:00:01 blood 2067 #> 4134 26.7 3 1921 1921-03-02 20:00:01 bone 2067 #> 4135 32.4 4 1921 1921-04-02 06:00:00 blood 2068 #> 4136 32.4 4 1921 1921-04-02 06:00:00 bone 2068 #> 4137 22.2 5 1921 1921-05-02 16:00:01 blood 2069 #> 4138 22.2 5 1921 1921-05-02 16:00:01 bone 2069 #> 4139 33.7 6 1921 1921-06-02 02:00:01 blood 2070 #> 4140 33.7 6 1921 1921-06-02 02:00:01 bone 2070 #> 4141 41.9 7 1921 1921-07-02 12:00:00 blood 2071 #> 4142 41.9 7 1921 1921-07-02 12:00:00 bone 2071 #> 4143 22.8 8 1921 1921-08-01 22:00:01 blood 2072 #> 4144 22.8 8 1921 1921-08-01 22:00:01 bone 2072 #> 4145 17.8 9 1921 1921-09-01 08:00:01 blood 2073 #> 4146 17.8 9 1921 1921-09-01 08:00:01 bone 2073 #> 4147 18.2 10 1921 1921-10-01 18:00:00 blood 2074 #> 4148 18.2 10 1921 1921-10-01 18:00:00 bone 2074 #> 4149 17.8 11 1921 1921-11-01 04:00:01 blood 2075 #> 4150 17.8 11 1921 1921-11-01 04:00:01 bone 2075 #> 4151 20.3 12 1921 1921-12-01 14:00:01 blood 2076 #> 4152 20.3 12 1921 1921-12-01 14:00:01 bone 2076 #> 4153 11.8 1 1922 1922-01-01 00:00:00 blood 2077 #> 4154 11.8 1 1922 1922-01-01 00:00:00 bone 2077 #> 4155 26.4 2 1922 1922-01-31 10:00:01 blood 2078 #> 4156 26.4 2 1922 1922-01-31 10:00:01 bone 2078 #> 4157 54.7 3 1922 1922-03-02 20:00:01 blood 2079 #> 4158 54.7 3 1922 1922-03-02 20:00:01 bone 2079 #> 4159 11.0 4 1922 1922-04-02 06:00:00 blood 2080 #> 4160 11.0 4 1922 1922-04-02 06:00:00 bone 2080 #> 4161 8.0 5 1922 1922-05-02 16:00:01 blood 2081 #> 4162 8.0 5 1922 1922-05-02 16:00:01 bone 2081 #> 4163 5.8 6 1922 1922-06-02 02:00:01 blood 2082 #> 4164 5.8 6 1922 1922-06-02 02:00:01 bone 2082 #> 4165 10.9 7 1922 1922-07-02 12:00:00 blood 2083 #> 4166 10.9 7 1922 1922-07-02 12:00:00 bone 2083 #> 4167 6.5 8 1922 1922-08-01 22:00:01 blood 2084 #> 4168 6.5 8 1922 1922-08-01 22:00:01 bone 2084 #> 4169 4.7 9 1922 1922-09-01 08:00:01 blood 2085 #> 4170 4.7 9 1922 1922-09-01 08:00:01 bone 2085 #> 4171 6.2 10 1922 1922-10-01 18:00:00 blood 2086 #> 4172 6.2 10 1922 1922-10-01 18:00:00 bone 2086 #> 4173 7.4 11 1922 1922-11-01 04:00:01 blood 2087 #> 4174 7.4 11 1922 1922-11-01 04:00:01 bone 2087 #> 4175 17.5 12 1922 1922-12-01 14:00:01 blood 2088 #> 4176 17.5 12 1922 1922-12-01 14:00:01 bone 2088 #> 4177 4.5 1 1923 1923-01-01 00:00:00 blood 2089 #> 4178 4.5 1 1923 1923-01-01 00:00:00 bone 2089 #> 4179 1.5 2 1923 1923-01-31 10:00:01 blood 2090 #> 4180 1.5 2 1923 1923-01-31 10:00:01 bone 2090 #> 4181 3.3 3 1923 1923-03-02 20:00:01 blood 2091 #> 4182 3.3 3 1923 1923-03-02 20:00:01 bone 2091 #> 4183 6.1 4 1923 1923-04-02 06:00:00 blood 2092 #> 4184 6.1 4 1923 1923-04-02 06:00:00 bone 2092 #> 4185 3.2 5 1923 1923-05-02 16:00:01 blood 2093 #> 4186 3.2 5 1923 1923-05-02 16:00:01 bone 2093 #> 4187 9.1 6 1923 1923-06-02 02:00:01 blood 2094 #> 4188 9.1 6 1923 1923-06-02 02:00:01 bone 2094 #> 4189 3.5 7 1923 1923-07-02 12:00:00 blood 2095 #> 4190 3.5 7 1923 1923-07-02 12:00:00 bone 2095 #> 4191 0.5 8 1923 1923-08-01 22:00:01 blood 2096 #> 4192 0.5 8 1923 1923-08-01 22:00:01 bone 2096 #> 4193 13.2 9 1923 1923-09-01 08:00:01 blood 2097 #> 4194 13.2 9 1923 1923-09-01 08:00:01 bone 2097 #> 4195 11.6 10 1923 1923-10-01 18:00:00 blood 2098 #> 4196 11.6 10 1923 1923-10-01 18:00:00 bone 2098 #> 4197 10.0 11 1923 1923-11-01 04:00:01 blood 2099 #> 4198 10.0 11 1923 1923-11-01 04:00:01 bone 2099 #> 4199 2.8 12 1923 1923-12-01 14:00:01 blood 2100 #> 4200 2.8 12 1923 1923-12-01 14:00:01 bone 2100 #> 4201 0.5 1 1924 1924-01-01 00:00:00 blood 2101 #> 4202 0.5 1 1924 1924-01-01 00:00:00 bone 2101 #> 4203 5.1 2 1924 1924-01-31 12:00:01 blood 2102 #> 4204 5.1 2 1924 1924-01-31 12:00:01 bone 2102 #> 4205 1.8 3 1924 1924-03-02 00:00:01 blood 2103 #> 4206 1.8 3 1924 1924-03-02 00:00:01 bone 2103 #> 4207 11.3 4 1924 1924-04-01 12:00:00 blood 2104 #> 4208 11.3 4 1924 1924-04-01 12:00:00 bone 2104 #> 4209 20.8 5 1924 1924-05-02 00:00:01 blood 2105 #> 4210 20.8 5 1924 1924-05-02 00:00:01 bone 2105 #> 4211 24.0 6 1924 1924-06-01 12:00:01 blood 2106 #> 4212 24.0 6 1924 1924-06-01 12:00:01 bone 2106 #> 4213 28.1 7 1924 1924-07-02 00:00:00 blood 2107 #> 4214 28.1 7 1924 1924-07-02 00:00:00 bone 2107 #> 4215 19.3 8 1924 1924-08-01 12:00:01 blood 2108 #> 4216 19.3 8 1924 1924-08-01 12:00:01 bone 2108 #> 4217 25.1 9 1924 1924-09-01 00:00:01 blood 2109 #> 4218 25.1 9 1924 1924-09-01 00:00:01 bone 2109 #> 4219 25.6 10 1924 1924-10-01 12:00:00 blood 2110 #> 4220 25.6 10 1924 1924-10-01 12:00:00 bone 2110 #> 4221 22.5 11 1924 1924-11-01 00:00:01 blood 2111 #> 4222 22.5 11 1924 1924-11-01 00:00:01 bone 2111 #> 4223 16.5 12 1924 1924-12-01 12:00:01 blood 2112 #> 4224 16.5 12 1924 1924-12-01 12:00:01 bone 2112 #> 4225 5.5 1 1925 1925-01-01 00:00:00 blood 2113 #> 4226 5.5 1 1925 1925-01-01 00:00:00 bone 2113 #> 4227 23.2 2 1925 1925-01-31 10:00:01 blood 2114 #> 4228 23.2 2 1925 1925-01-31 10:00:01 bone 2114 #> 4229 18.0 3 1925 1925-03-02 20:00:01 blood 2115 #> 4230 18.0 3 1925 1925-03-02 20:00:01 bone 2115 #> 4231 31.7 4 1925 1925-04-02 06:00:00 blood 2116 #> 4232 31.7 4 1925 1925-04-02 06:00:00 bone 2116 #> 4233 42.8 5 1925 1925-05-02 16:00:01 blood 2117 #> 4234 42.8 5 1925 1925-05-02 16:00:01 bone 2117 #> 4235 47.5 6 1925 1925-06-02 02:00:01 blood 2118 #> 4236 47.5 6 1925 1925-06-02 02:00:01 bone 2118 #> 4237 38.5 7 1925 1925-07-02 12:00:00 blood 2119 #> 4238 38.5 7 1925 1925-07-02 12:00:00 bone 2119 #> 4239 37.9 8 1925 1925-08-01 22:00:01 blood 2120 #> 4240 37.9 8 1925 1925-08-01 22:00:01 bone 2120 #> 4241 60.2 9 1925 1925-09-01 08:00:01 blood 2121 #> 4242 60.2 9 1925 1925-09-01 08:00:01 bone 2121 #> 4243 69.2 10 1925 1925-10-01 18:00:00 blood 2122 #> 4244 69.2 10 1925 1925-10-01 18:00:00 bone 2122 #> 4245 58.6 11 1925 1925-11-01 04:00:01 blood 2123 #> 4246 58.6 11 1925 1925-11-01 04:00:01 bone 2123 #> 4247 98.6 12 1925 1925-12-01 14:00:01 blood 2124 #> 4248 98.6 12 1925 1925-12-01 14:00:01 bone 2124 #> 4249 71.8 1 1926 1926-01-01 00:00:00 blood 2125 #> 4250 71.8 1 1926 1926-01-01 00:00:00 bone 2125 #> 4251 70.0 2 1926 1926-01-31 10:00:01 blood 2126 #> 4252 70.0 2 1926 1926-01-31 10:00:01 bone 2126 #> 4253 62.5 3 1926 1926-03-02 20:00:01 blood 2127 #> 4254 62.5 3 1926 1926-03-02 20:00:01 bone 2127 #> 4255 38.5 4 1926 1926-04-02 06:00:00 blood 2128 #> 4256 38.5 4 1926 1926-04-02 06:00:00 bone 2128 #> 4257 64.3 5 1926 1926-05-02 16:00:01 blood 2129 #> 4258 64.3 5 1926 1926-05-02 16:00:01 bone 2129 #> 4259 73.5 6 1926 1926-06-02 02:00:01 blood 2130 #> 4260 73.5 6 1926 1926-06-02 02:00:01 bone 2130 #> 4261 52.3 7 1926 1926-07-02 12:00:00 blood 2131 #> 4262 52.3 7 1926 1926-07-02 12:00:00 bone 2131 #> 4263 61.6 8 1926 1926-08-01 22:00:01 blood 2132 #> 4264 61.6 8 1926 1926-08-01 22:00:01 bone 2132 #> 4265 60.8 9 1926 1926-09-01 08:00:01 blood 2133 #> 4266 60.8 9 1926 1926-09-01 08:00:01 bone 2133 #> 4267 71.5 10 1926 1926-10-01 18:00:00 blood 2134 #> 4268 71.5 10 1926 1926-10-01 18:00:00 bone 2134 #> 4269 60.5 11 1926 1926-11-01 04:00:01 blood 2135 #> 4270 60.5 11 1926 1926-11-01 04:00:01 bone 2135 #> 4271 79.4 12 1926 1926-12-01 14:00:01 blood 2136 #> 4272 79.4 12 1926 1926-12-01 14:00:01 bone 2136 #> 4273 81.6 1 1927 1927-01-01 00:00:00 blood 2137 #> 4274 81.6 1 1927 1927-01-01 00:00:00 bone 2137 #> 4275 93.0 2 1927 1927-01-31 10:00:01 blood 2138 #> 4276 93.0 2 1927 1927-01-31 10:00:01 bone 2138 #> 4277 69.6 3 1927 1927-03-02 20:00:01 blood 2139 #> 4278 69.6 3 1927 1927-03-02 20:00:01 bone 2139 #> 4279 93.5 4 1927 1927-04-02 06:00:00 blood 2140 #> 4280 93.5 4 1927 1927-04-02 06:00:00 bone 2140 #> 4281 79.1 5 1927 1927-05-02 16:00:01 blood 2141 #> 4282 79.1 5 1927 1927-05-02 16:00:01 bone 2141 #> 4283 59.1 6 1927 1927-06-02 02:00:01 blood 2142 #> 4284 59.1 6 1927 1927-06-02 02:00:01 bone 2142 #> 4285 54.9 7 1927 1927-07-02 12:00:00 blood 2143 #> 4286 54.9 7 1927 1927-07-02 12:00:00 bone 2143 #> 4287 53.8 8 1927 1927-08-01 22:00:01 blood 2144 #> 4288 53.8 8 1927 1927-08-01 22:00:01 bone 2144 #> 4289 68.4 9 1927 1927-09-01 08:00:01 blood 2145 #> 4290 68.4 9 1927 1927-09-01 08:00:01 bone 2145 #> 4291 63.1 10 1927 1927-10-01 18:00:00 blood 2146 #> 4292 63.1 10 1927 1927-10-01 18:00:00 bone 2146 #> 4293 67.2 11 1927 1927-11-01 04:00:01 blood 2147 #> 4294 67.2 11 1927 1927-11-01 04:00:01 bone 2147 #> 4295 45.2 12 1927 1927-12-01 14:00:01 blood 2148 #> 4296 45.2 12 1927 1927-12-01 14:00:01 bone 2148 #> 4297 83.5 1 1928 1928-01-01 00:00:00 blood 2149 #> 4298 83.5 1 1928 1928-01-01 00:00:00 bone 2149 #> 4299 73.5 2 1928 1928-01-31 12:00:01 blood 2150 #> 4300 73.5 2 1928 1928-01-31 12:00:01 bone 2150 #> 4301 85.4 3 1928 1928-03-02 00:00:01 blood 2151 #> 4302 85.4 3 1928 1928-03-02 00:00:01 bone 2151 #> 4303 80.6 4 1928 1928-04-01 12:00:00 blood 2152 #> 4304 80.6 4 1928 1928-04-01 12:00:00 bone 2152 #> 4305 76.9 5 1928 1928-05-02 00:00:01 blood 2153 #> 4306 76.9 5 1928 1928-05-02 00:00:01 bone 2153 #> 4307 91.4 6 1928 1928-06-01 12:00:01 blood 2154 #> 4308 91.4 6 1928 1928-06-01 12:00:01 bone 2154 #> 4309 98.0 7 1928 1928-07-02 00:00:00 blood 2155 #> 4310 98.0 7 1928 1928-07-02 00:00:00 bone 2155 #> 4311 83.8 8 1928 1928-08-01 12:00:01 blood 2156 #> 4312 83.8 8 1928 1928-08-01 12:00:01 bone 2156 #> 4313 89.7 9 1928 1928-09-01 00:00:01 blood 2157 #> 4314 89.7 9 1928 1928-09-01 00:00:01 bone 2157 #> 4315 61.4 10 1928 1928-10-01 12:00:00 blood 2158 #> 4316 61.4 10 1928 1928-10-01 12:00:00 bone 2158 #> 4317 50.3 11 1928 1928-11-01 00:00:01 blood 2159 #> 4318 50.3 11 1928 1928-11-01 00:00:01 bone 2159 #> 4319 59.0 12 1928 1928-12-01 12:00:01 blood 2160 #> 4320 59.0 12 1928 1928-12-01 12:00:01 bone 2160 #> 4321 68.9 1 1929 1929-01-01 00:00:00 blood 2161 #> 4322 68.9 1 1929 1929-01-01 00:00:00 bone 2161 #> 4323 64.1 2 1929 1929-01-31 10:00:01 blood 2162 #> 4324 64.1 2 1929 1929-01-31 10:00:01 bone 2162 #> 4325 50.2 3 1929 1929-03-02 20:00:01 blood 2163 #> 4326 50.2 3 1929 1929-03-02 20:00:01 bone 2163 #> 4327 52.8 4 1929 1929-04-02 06:00:00 blood 2164 #> 4328 52.8 4 1929 1929-04-02 06:00:00 bone 2164 #> 4329 58.2 5 1929 1929-05-02 16:00:01 blood 2165 #> 4330 58.2 5 1929 1929-05-02 16:00:01 bone 2165 #> 4331 71.9 6 1929 1929-06-02 02:00:01 blood 2166 #> 4332 71.9 6 1929 1929-06-02 02:00:01 bone 2166 #> 4333 70.2 7 1929 1929-07-02 12:00:00 blood 2167 #> 4334 70.2 7 1929 1929-07-02 12:00:00 bone 2167 #> 4335 65.8 8 1929 1929-08-01 22:00:01 blood 2168 #> 4336 65.8 8 1929 1929-08-01 22:00:01 bone 2168 #> 4337 34.4 9 1929 1929-09-01 08:00:01 blood 2169 #> 4338 34.4 9 1929 1929-09-01 08:00:01 bone 2169 #> 4339 54.0 10 1929 1929-10-01 18:00:00 blood 2170 #> 4340 54.0 10 1929 1929-10-01 18:00:00 bone 2170 #> 4341 81.1 11 1929 1929-11-01 04:00:01 blood 2171 #> 4342 81.1 11 1929 1929-11-01 04:00:01 bone 2171 #> 4343 108.0 12 1929 1929-12-01 14:00:01 blood 2172 #> 4344 108.0 12 1929 1929-12-01 14:00:01 bone 2172 #> 4345 65.3 1 1930 1930-01-01 00:00:00 blood 2173 #> 4346 65.3 1 1930 1930-01-01 00:00:00 bone 2173 #> 4347 49.2 2 1930 1930-01-31 10:00:01 blood 2174 #> 4348 49.2 2 1930 1930-01-31 10:00:01 bone 2174 #> 4349 35.0 3 1930 1930-03-02 20:00:01 blood 2175 #> 4350 35.0 3 1930 1930-03-02 20:00:01 bone 2175 #> 4351 38.2 4 1930 1930-04-02 06:00:00 blood 2176 #> 4352 38.2 4 1930 1930-04-02 06:00:00 bone 2176 #> 4353 36.8 5 1930 1930-05-02 16:00:01 blood 2177 #> 4354 36.8 5 1930 1930-05-02 16:00:01 bone 2177 #> 4355 28.8 6 1930 1930-06-02 02:00:01 blood 2178 #> 4356 28.8 6 1930 1930-06-02 02:00:01 bone 2178 #> 4357 21.9 7 1930 1930-07-02 12:00:00 blood 2179 #> 4358 21.9 7 1930 1930-07-02 12:00:00 bone 2179 #> 4359 24.9 8 1930 1930-08-01 22:00:01 blood 2180 #> 4360 24.9 8 1930 1930-08-01 22:00:01 bone 2180 #> 4361 32.1 9 1930 1930-09-01 08:00:01 blood 2181 #> 4362 32.1 9 1930 1930-09-01 08:00:01 bone 2181 #> 4363 34.4 10 1930 1930-10-01 18:00:00 blood 2182 #> 4364 34.4 10 1930 1930-10-01 18:00:00 bone 2182 #> 4365 35.6 11 1930 1930-11-01 04:00:01 blood 2183 #> 4366 35.6 11 1930 1930-11-01 04:00:01 bone 2183 #> 4367 25.8 12 1930 1930-12-01 14:00:01 blood 2184 #> 4368 25.8 12 1930 1930-12-01 14:00:01 bone 2184 #> 4369 14.6 1 1931 1931-01-01 00:00:00 blood 2185 #> 4370 14.6 1 1931 1931-01-01 00:00:00 bone 2185 #> 4371 43.1 2 1931 1931-01-31 10:00:01 blood 2186 #> 4372 43.1 2 1931 1931-01-31 10:00:01 bone 2186 #> 4373 30.0 3 1931 1931-03-02 20:00:01 blood 2187 #> 4374 30.0 3 1931 1931-03-02 20:00:01 bone 2187 #> 4375 31.2 4 1931 1931-04-02 06:00:00 blood 2188 #> 4376 31.2 4 1931 1931-04-02 06:00:00 bone 2188 #> 4377 24.6 5 1931 1931-05-02 16:00:01 blood 2189 #> 4378 24.6 5 1931 1931-05-02 16:00:01 bone 2189 #> 4379 15.3 6 1931 1931-06-02 02:00:01 blood 2190 #> 4380 15.3 6 1931 1931-06-02 02:00:01 bone 2190 #> 4381 17.4 7 1931 1931-07-02 12:00:00 blood 2191 #> 4382 17.4 7 1931 1931-07-02 12:00:00 bone 2191 #> 4383 13.0 8 1931 1931-08-01 22:00:01 blood 2192 #> 4384 13.0 8 1931 1931-08-01 22:00:01 bone 2192 #> 4385 19.0 9 1931 1931-09-01 08:00:01 blood 2193 #> 4386 19.0 9 1931 1931-09-01 08:00:01 bone 2193 #> 4387 10.0 10 1931 1931-10-01 18:00:00 blood 2194 #> 4388 10.0 10 1931 1931-10-01 18:00:00 bone 2194 #> 4389 18.7 11 1931 1931-11-01 04:00:01 blood 2195 #> 4390 18.7 11 1931 1931-11-01 04:00:01 bone 2195 #> 4391 17.8 12 1931 1931-12-01 14:00:01 blood 2196 #> 4392 17.8 12 1931 1931-12-01 14:00:01 bone 2196 #> 4393 12.1 1 1932 1932-01-01 00:00:00 blood 2197 #> 4394 12.1 1 1932 1932-01-01 00:00:00 bone 2197 #> 4395 10.6 2 1932 1932-01-31 12:00:01 blood 2198 #> 4396 10.6 2 1932 1932-01-31 12:00:01 bone 2198 #> 4397 11.2 3 1932 1932-03-02 00:00:01 blood 2199 #> 4398 11.2 3 1932 1932-03-02 00:00:01 bone 2199 #> 4399 11.2 4 1932 1932-04-01 12:00:00 blood 2200 #> 4400 11.2 4 1932 1932-04-01 12:00:00 bone 2200 #> 4401 17.9 5 1932 1932-05-02 00:00:01 blood 2201 #> 4402 17.9 5 1932 1932-05-02 00:00:01 bone 2201 #> 4403 22.2 6 1932 1932-06-01 12:00:01 blood 2202 #> 4404 22.2 6 1932 1932-06-01 12:00:01 bone 2202 #> 4405 9.6 7 1932 1932-07-02 00:00:00 blood 2203 #> 4406 9.6 7 1932 1932-07-02 00:00:00 bone 2203 #> 4407 6.8 8 1932 1932-08-01 12:00:01 blood 2204 #> 4408 6.8 8 1932 1932-08-01 12:00:01 bone 2204 #> 4409 4.0 9 1932 1932-09-01 00:00:01 blood 2205 #> 4410 4.0 9 1932 1932-09-01 00:00:01 bone 2205 #> 4411 8.9 10 1932 1932-10-01 12:00:00 blood 2206 #> 4412 8.9 10 1932 1932-10-01 12:00:00 bone 2206 #> 4413 8.2 11 1932 1932-11-01 00:00:01 blood 2207 #> 4414 8.2 11 1932 1932-11-01 00:00:01 bone 2207 #> 4415 11.0 12 1932 1932-12-01 12:00:01 blood 2208 #> 4416 11.0 12 1932 1932-12-01 12:00:01 bone 2208 #> 4417 12.3 1 1933 1933-01-01 00:00:00 blood 2209 #> 4418 12.3 1 1933 1933-01-01 00:00:00 bone 2209 #> 4419 22.2 2 1933 1933-01-31 10:00:01 blood 2210 #> 4420 22.2 2 1933 1933-01-31 10:00:01 bone 2210 #> 4421 10.1 3 1933 1933-03-02 20:00:01 blood 2211 #> 4422 10.1 3 1933 1933-03-02 20:00:01 bone 2211 #> 4423 2.9 4 1933 1933-04-02 06:00:00 blood 2212 #> 4424 2.9 4 1933 1933-04-02 06:00:00 bone 2212 #> 4425 3.2 5 1933 1933-05-02 16:00:01 blood 2213 #> 4426 3.2 5 1933 1933-05-02 16:00:01 bone 2213 #> 4427 5.2 6 1933 1933-06-02 02:00:01 blood 2214 #> 4428 5.2 6 1933 1933-06-02 02:00:01 bone 2214 #> 4429 2.8 7 1933 1933-07-02 12:00:00 blood 2215 #> 4430 2.8 7 1933 1933-07-02 12:00:00 bone 2215 #> 4431 0.2 8 1933 1933-08-01 22:00:01 blood 2216 #> 4432 0.2 8 1933 1933-08-01 22:00:01 bone 2216 #> 4433 5.1 9 1933 1933-09-01 08:00:01 blood 2217 #> 4434 5.1 9 1933 1933-09-01 08:00:01 bone 2217 #> 4435 3.0 10 1933 1933-10-01 18:00:00 blood 2218 #> 4436 3.0 10 1933 1933-10-01 18:00:00 bone 2218 #> 4437 0.6 11 1933 1933-11-01 04:00:01 blood 2219 #> 4438 0.6 11 1933 1933-11-01 04:00:01 bone 2219 #> 4439 0.3 12 1933 1933-12-01 14:00:01 blood 2220 #> 4440 0.3 12 1933 1933-12-01 14:00:01 bone 2220 #> 4441 3.4 1 1934 1934-01-01 00:00:00 blood 2221 #> 4442 3.4 1 1934 1934-01-01 00:00:00 bone 2221 #> 4443 7.8 2 1934 1934-01-31 10:00:01 blood 2222 #> 4444 7.8 2 1934 1934-01-31 10:00:01 bone 2222 #> 4445 4.3 3 1934 1934-03-02 20:00:01 blood 2223 #> 4446 4.3 3 1934 1934-03-02 20:00:01 bone 2223 #> 4447 11.3 4 1934 1934-04-02 06:00:00 blood 2224 #> 4448 11.3 4 1934 1934-04-02 06:00:00 bone 2224 #> 4449 19.7 5 1934 1934-05-02 16:00:01 blood 2225 #> 4450 19.7 5 1934 1934-05-02 16:00:01 bone 2225 #> 4451 6.7 6 1934 1934-06-02 02:00:01 blood 2226 #> 4452 6.7 6 1934 1934-06-02 02:00:01 bone 2226 #> 4453 9.3 7 1934 1934-07-02 12:00:00 blood 2227 #> 4454 9.3 7 1934 1934-07-02 12:00:00 bone 2227 #> 4455 8.3 8 1934 1934-08-01 22:00:01 blood 2228 #> 4456 8.3 8 1934 1934-08-01 22:00:01 bone 2228 #> 4457 4.0 9 1934 1934-09-01 08:00:01 blood 2229 #> 4458 4.0 9 1934 1934-09-01 08:00:01 bone 2229 #> 4459 5.7 10 1934 1934-10-01 18:00:00 blood 2230 #> 4460 5.7 10 1934 1934-10-01 18:00:00 bone 2230 #> 4461 8.7 11 1934 1934-11-01 04:00:01 blood 2231 #> 4462 8.7 11 1934 1934-11-01 04:00:01 bone 2231 #> 4463 15.4 12 1934 1934-12-01 14:00:01 blood 2232 #> 4464 15.4 12 1934 1934-12-01 14:00:01 bone 2232 #> 4465 18.9 1 1935 1935-01-01 00:00:00 blood 2233 #> 4466 18.9 1 1935 1935-01-01 00:00:00 bone 2233 #> 4467 20.5 2 1935 1935-01-31 10:00:01 blood 2234 #> 4468 20.5 2 1935 1935-01-31 10:00:01 bone 2234 #> 4469 23.1 3 1935 1935-03-02 20:00:01 blood 2235 #> 4470 23.1 3 1935 1935-03-02 20:00:01 bone 2235 #> 4471 12.2 4 1935 1935-04-02 06:00:00 blood 2236 #> 4472 12.2 4 1935 1935-04-02 06:00:00 bone 2236 #> 4473 27.3 5 1935 1935-05-02 16:00:01 blood 2237 #> 4474 27.3 5 1935 1935-05-02 16:00:01 bone 2237 #> 4475 45.7 6 1935 1935-06-02 02:00:01 blood 2238 #> 4476 45.7 6 1935 1935-06-02 02:00:01 bone 2238 #> 4477 33.9 7 1935 1935-07-02 12:00:00 blood 2239 #> 4478 33.9 7 1935 1935-07-02 12:00:00 bone 2239 #> 4479 30.1 8 1935 1935-08-01 22:00:01 blood 2240 #> 4480 30.1 8 1935 1935-08-01 22:00:01 bone 2240 #> 4481 42.1 9 1935 1935-09-01 08:00:01 blood 2241 #> 4482 42.1 9 1935 1935-09-01 08:00:01 bone 2241 #> 4483 53.2 10 1935 1935-10-01 18:00:00 blood 2242 #> 4484 53.2 10 1935 1935-10-01 18:00:00 bone 2242 #> 4485 64.2 11 1935 1935-11-01 04:00:01 blood 2243 #> 4486 64.2 11 1935 1935-11-01 04:00:01 bone 2243 #> 4487 61.5 12 1935 1935-12-01 14:00:01 blood 2244 #> 4488 61.5 12 1935 1935-12-01 14:00:01 bone 2244 #> 4489 62.8 1 1936 1936-01-01 00:00:00 blood 2245 #> 4490 62.8 1 1936 1936-01-01 00:00:00 bone 2245 #> 4491 74.3 2 1936 1936-01-31 12:00:01 blood 2246 #> 4492 74.3 2 1936 1936-01-31 12:00:01 bone 2246 #> 4493 77.1 3 1936 1936-03-02 00:00:01 blood 2247 #> 4494 77.1 3 1936 1936-03-02 00:00:01 bone 2247 #> 4495 74.9 4 1936 1936-04-01 12:00:00 blood 2248 #> 4496 74.9 4 1936 1936-04-01 12:00:00 bone 2248 #> 4497 54.6 5 1936 1936-05-02 00:00:01 blood 2249 #> 4498 54.6 5 1936 1936-05-02 00:00:01 bone 2249 #> 4499 70.0 6 1936 1936-06-01 12:00:01 blood 2250 #> 4500 70.0 6 1936 1936-06-01 12:00:01 bone 2250 #> 4501 52.3 7 1936 1936-07-02 00:00:00 blood 2251 #> 4502 52.3 7 1936 1936-07-02 00:00:00 bone 2251 #> 4503 87.0 8 1936 1936-08-01 12:00:01 blood 2252 #> 4504 87.0 8 1936 1936-08-01 12:00:01 bone 2252 #> 4505 76.0 9 1936 1936-09-01 00:00:01 blood 2253 #> 4506 76.0 9 1936 1936-09-01 00:00:01 bone 2253 #> 4507 89.0 10 1936 1936-10-01 12:00:00 blood 2254 #> 4508 89.0 10 1936 1936-10-01 12:00:00 bone 2254 #> 4509 115.4 11 1936 1936-11-01 00:00:01 blood 2255 #> 4510 115.4 11 1936 1936-11-01 00:00:01 bone 2255 #> 4511 123.4 12 1936 1936-12-01 12:00:01 blood 2256 #> 4512 123.4 12 1936 1936-12-01 12:00:01 bone 2256 #> 4513 132.5 1 1937 1937-01-01 00:00:00 blood 2257 #> 4514 132.5 1 1937 1937-01-01 00:00:00 bone 2257 #> 4515 128.5 2 1937 1937-01-31 10:00:01 blood 2258 #> 4516 128.5 2 1937 1937-01-31 10:00:01 bone 2258 #> 4517 83.9 3 1937 1937-03-02 20:00:01 blood 2259 #> 4518 83.9 3 1937 1937-03-02 20:00:01 bone 2259 #> 4519 109.3 4 1937 1937-04-02 06:00:00 blood 2260 #> 4520 109.3 4 1937 1937-04-02 06:00:00 bone 2260 #> 4521 116.7 5 1937 1937-05-02 16:00:01 blood 2261 #> 4522 116.7 5 1937 1937-05-02 16:00:01 bone 2261 #> 4523 130.3 6 1937 1937-06-02 02:00:01 blood 2262 #> 4524 130.3 6 1937 1937-06-02 02:00:01 bone 2262 #> 4525 145.1 7 1937 1937-07-02 12:00:00 blood 2263 #> 4526 145.1 7 1937 1937-07-02 12:00:00 bone 2263 #> 4527 137.7 8 1937 1937-08-01 22:00:01 blood 2264 #> 4528 137.7 8 1937 1937-08-01 22:00:01 bone 2264 #> 4529 100.7 9 1937 1937-09-01 08:00:01 blood 2265 #> 4530 100.7 9 1937 1937-09-01 08:00:01 bone 2265 #> 4531 124.9 10 1937 1937-10-01 18:00:00 blood 2266 #> 4532 124.9 10 1937 1937-10-01 18:00:00 bone 2266 #> 4533 74.4 11 1937 1937-11-01 04:00:01 blood 2267 #> 4534 74.4 11 1937 1937-11-01 04:00:01 bone 2267 #> 4535 88.8 12 1937 1937-12-01 14:00:01 blood 2268 #> 4536 88.8 12 1937 1937-12-01 14:00:01 bone 2268 #> 4537 98.4 1 1938 1938-01-01 00:00:00 blood 2269 #> 4538 98.4 1 1938 1938-01-01 00:00:00 bone 2269 #> 4539 119.2 2 1938 1938-01-31 10:00:01 blood 2270 #> 4540 119.2 2 1938 1938-01-31 10:00:01 bone 2270 #> 4541 86.5 3 1938 1938-03-02 20:00:01 blood 2271 #> 4542 86.5 3 1938 1938-03-02 20:00:01 bone 2271 #> 4543 101.0 4 1938 1938-04-02 06:00:00 blood 2272 #> 4544 101.0 4 1938 1938-04-02 06:00:00 bone 2272 #> 4545 127.4 5 1938 1938-05-02 16:00:01 blood 2273 #> 4546 127.4 5 1938 1938-05-02 16:00:01 bone 2273 #> 4547 97.5 6 1938 1938-06-02 02:00:01 blood 2274 #> 4548 97.5 6 1938 1938-06-02 02:00:01 bone 2274 #> 4549 165.3 7 1938 1938-07-02 12:00:00 blood 2275 #> 4550 165.3 7 1938 1938-07-02 12:00:00 bone 2275 #> 4551 115.7 8 1938 1938-08-01 22:00:01 blood 2276 #> 4552 115.7 8 1938 1938-08-01 22:00:01 bone 2276 #> 4553 89.6 9 1938 1938-09-01 08:00:01 blood 2277 #> 4554 89.6 9 1938 1938-09-01 08:00:01 bone 2277 #> 4555 99.1 10 1938 1938-10-01 18:00:00 blood 2278 #> 4556 99.1 10 1938 1938-10-01 18:00:00 bone 2278 #> 4557 122.2 11 1938 1938-11-01 04:00:01 blood 2279 #> 4558 122.2 11 1938 1938-11-01 04:00:01 bone 2279 #> 4559 92.7 12 1938 1938-12-01 14:00:01 blood 2280 #> 4560 92.7 12 1938 1938-12-01 14:00:01 bone 2280 #> 4561 80.3 1 1939 1939-01-01 00:00:00 blood 2281 #> 4562 80.3 1 1939 1939-01-01 00:00:00 bone 2281 #> 4563 77.4 2 1939 1939-01-31 10:00:01 blood 2282 #> 4564 77.4 2 1939 1939-01-31 10:00:01 bone 2282 #> 4565 64.6 3 1939 1939-03-02 20:00:01 blood 2283 #> 4566 64.6 3 1939 1939-03-02 20:00:01 bone 2283 #> 4567 109.1 4 1939 1939-04-02 06:00:00 blood 2284 #> 4568 109.1 4 1939 1939-04-02 06:00:00 bone 2284 #> 4569 118.3 5 1939 1939-05-02 16:00:01 blood 2285 #> 4570 118.3 5 1939 1939-05-02 16:00:01 bone 2285 #> 4571 101.0 6 1939 1939-06-02 02:00:01 blood 2286 #> 4572 101.0 6 1939 1939-06-02 02:00:01 bone 2286 #> 4573 97.6 7 1939 1939-07-02 12:00:00 blood 2287 #> 4574 97.6 7 1939 1939-07-02 12:00:00 bone 2287 #> 4575 105.8 8 1939 1939-08-01 22:00:01 blood 2288 #> 4576 105.8 8 1939 1939-08-01 22:00:01 bone 2288 #> 4577 112.6 9 1939 1939-09-01 08:00:01 blood 2289 #> 4578 112.6 9 1939 1939-09-01 08:00:01 bone 2289 #> 4579 88.1 10 1939 1939-10-01 18:00:00 blood 2290 #> 4580 88.1 10 1939 1939-10-01 18:00:00 bone 2290 #> 4581 68.1 11 1939 1939-11-01 04:00:01 blood 2291 #> 4582 68.1 11 1939 1939-11-01 04:00:01 bone 2291 #> 4583 42.1 12 1939 1939-12-01 14:00:01 blood 2292 #> 4584 42.1 12 1939 1939-12-01 14:00:01 bone 2292 #> 4585 50.5 1 1940 1940-01-01 00:00:00 blood 2293 #> 4586 50.5 1 1940 1940-01-01 00:00:00 bone 2293 #> 4587 59.4 2 1940 1940-01-31 12:00:01 blood 2294 #> 4588 59.4 2 1940 1940-01-31 12:00:01 bone 2294 #> 4589 83.3 3 1940 1940-03-02 00:00:01 blood 2295 #> 4590 83.3 3 1940 1940-03-02 00:00:01 bone 2295 #> 4591 60.7 4 1940 1940-04-01 12:00:00 blood 2296 #> 4592 60.7 4 1940 1940-04-01 12:00:00 bone 2296 #> 4593 54.4 5 1940 1940-05-02 00:00:01 blood 2297 #> 4594 54.4 5 1940 1940-05-02 00:00:01 bone 2297 #> 4595 83.9 6 1940 1940-06-01 12:00:01 blood 2298 #> 4596 83.9 6 1940 1940-06-01 12:00:01 bone 2298 #> 4597 67.5 7 1940 1940-07-02 00:00:00 blood 2299 #> 4598 67.5 7 1940 1940-07-02 00:00:00 bone 2299 #> 4599 105.5 8 1940 1940-08-01 12:00:01 blood 2300 #> 4600 105.5 8 1940 1940-08-01 12:00:01 bone 2300 #> 4601 66.5 9 1940 1940-09-01 00:00:01 blood 2301 #> 4602 66.5 9 1940 1940-09-01 00:00:01 bone 2301 #> 4603 55.0 10 1940 1940-10-01 12:00:00 blood 2302 #> 4604 55.0 10 1940 1940-10-01 12:00:00 bone 2302 #> 4605 58.4 11 1940 1940-11-01 00:00:01 blood 2303 #> 4606 58.4 11 1940 1940-11-01 00:00:01 bone 2303 #> 4607 68.3 12 1940 1940-12-01 12:00:01 blood 2304 #> 4608 68.3 12 1940 1940-12-01 12:00:01 bone 2304 #> 4609 45.6 1 1941 1941-01-01 00:00:00 blood 2305 #> 4610 45.6 1 1941 1941-01-01 00:00:00 bone 2305 #> 4611 44.5 2 1941 1941-01-31 10:00:01 blood 2306 #> 4612 44.5 2 1941 1941-01-31 10:00:01 bone 2306 #> 4613 46.4 3 1941 1941-03-02 20:00:01 blood 2307 #> 4614 46.4 3 1941 1941-03-02 20:00:01 bone 2307 #> 4615 32.8 4 1941 1941-04-02 06:00:00 blood 2308 #> 4616 32.8 4 1941 1941-04-02 06:00:00 bone 2308 #> 4617 29.5 5 1941 1941-05-02 16:00:01 blood 2309 #> 4618 29.5 5 1941 1941-05-02 16:00:01 bone 2309 #> 4619 59.8 6 1941 1941-06-02 02:00:01 blood 2310 #> 4620 59.8 6 1941 1941-06-02 02:00:01 bone 2310 #> 4621 66.9 7 1941 1941-07-02 12:00:00 blood 2311 #> 4622 66.9 7 1941 1941-07-02 12:00:00 bone 2311 #> 4623 60.0 8 1941 1941-08-01 22:00:01 blood 2312 #> 4624 60.0 8 1941 1941-08-01 22:00:01 bone 2312 #> 4625 65.9 9 1941 1941-09-01 08:00:01 blood 2313 #> 4626 65.9 9 1941 1941-09-01 08:00:01 bone 2313 #> 4627 46.3 10 1941 1941-10-01 18:00:00 blood 2314 #> 4628 46.3 10 1941 1941-10-01 18:00:00 bone 2314 #> 4629 38.3 11 1941 1941-11-01 04:00:01 blood 2315 #> 4630 38.3 11 1941 1941-11-01 04:00:01 bone 2315 #> 4631 33.7 12 1941 1941-12-01 14:00:01 blood 2316 #> 4632 33.7 12 1941 1941-12-01 14:00:01 bone 2316 #> 4633 35.6 1 1942 1942-01-01 00:00:00 blood 2317 #> 4634 35.6 1 1942 1942-01-01 00:00:00 bone 2317 #> 4635 52.8 2 1942 1942-01-31 10:00:01 blood 2318 #> 4636 52.8 2 1942 1942-01-31 10:00:01 bone 2318 #> 4637 54.2 3 1942 1942-03-02 20:00:01 blood 2319 #> 4638 54.2 3 1942 1942-03-02 20:00:01 bone 2319 #> 4639 60.7 4 1942 1942-04-02 06:00:00 blood 2320 #> 4640 60.7 4 1942 1942-04-02 06:00:00 bone 2320 #> 4641 25.0 5 1942 1942-05-02 16:00:01 blood 2321 #> 4642 25.0 5 1942 1942-05-02 16:00:01 bone 2321 #> 4643 11.4 6 1942 1942-06-02 02:00:01 blood 2322 #> 4644 11.4 6 1942 1942-06-02 02:00:01 bone 2322 #> 4645 17.7 7 1942 1942-07-02 12:00:00 blood 2323 #> 4646 17.7 7 1942 1942-07-02 12:00:00 bone 2323 #> 4647 20.2 8 1942 1942-08-01 22:00:01 blood 2324 #> 4648 20.2 8 1942 1942-08-01 22:00:01 bone 2324 #> 4649 17.2 9 1942 1942-09-01 08:00:01 blood 2325 #> 4650 17.2 9 1942 1942-09-01 08:00:01 bone 2325 #> 4651 19.2 10 1942 1942-10-01 18:00:00 blood 2326 #> 4652 19.2 10 1942 1942-10-01 18:00:00 bone 2326 #> 4653 30.7 11 1942 1942-11-01 04:00:01 blood 2327 #> 4654 30.7 11 1942 1942-11-01 04:00:01 bone 2327 #> 4655 22.5 12 1942 1942-12-01 14:00:01 blood 2328 #> 4656 22.5 12 1942 1942-12-01 14:00:01 bone 2328 #> 4657 12.4 1 1943 1943-01-01 00:00:00 blood 2329 #> 4658 12.4 1 1943 1943-01-01 00:00:00 bone 2329 #> 4659 28.9 2 1943 1943-01-31 10:00:01 blood 2330 #> 4660 28.9 2 1943 1943-01-31 10:00:01 bone 2330 #> 4661 27.4 3 1943 1943-03-02 20:00:01 blood 2331 #> 4662 27.4 3 1943 1943-03-02 20:00:01 bone 2331 #> 4663 26.1 4 1943 1943-04-02 06:00:00 blood 2332 #> 4664 26.1 4 1943 1943-04-02 06:00:00 bone 2332 #> 4665 14.1 5 1943 1943-05-02 16:00:01 blood 2333 #> 4666 14.1 5 1943 1943-05-02 16:00:01 bone 2333 #> 4667 7.6 6 1943 1943-06-02 02:00:01 blood 2334 #> 4668 7.6 6 1943 1943-06-02 02:00:01 bone 2334 #> 4669 13.2 7 1943 1943-07-02 12:00:00 blood 2335 #> 4670 13.2 7 1943 1943-07-02 12:00:00 bone 2335 #> 4671 19.4 8 1943 1943-08-01 22:00:01 blood 2336 #> 4672 19.4 8 1943 1943-08-01 22:00:01 bone 2336 #> 4673 10.0 9 1943 1943-09-01 08:00:01 blood 2337 #> 4674 10.0 9 1943 1943-09-01 08:00:01 bone 2337 #> 4675 7.8 10 1943 1943-10-01 18:00:00 blood 2338 #> 4676 7.8 10 1943 1943-10-01 18:00:00 bone 2338 #> 4677 10.2 11 1943 1943-11-01 04:00:01 blood 2339 #> 4678 10.2 11 1943 1943-11-01 04:00:01 bone 2339 #> 4679 18.8 12 1943 1943-12-01 14:00:01 blood 2340 #> 4680 18.8 12 1943 1943-12-01 14:00:01 bone 2340 #> 4681 3.7 1 1944 1944-01-01 00:00:00 blood 2341 #> 4682 3.7 1 1944 1944-01-01 00:00:00 bone 2341 #> 4683 0.5 2 1944 1944-01-31 12:00:01 blood 2342 #> 4684 0.5 2 1944 1944-01-31 12:00:01 bone 2342 #> 4685 11.0 3 1944 1944-03-02 00:00:01 blood 2343 #> 4686 11.0 3 1944 1944-03-02 00:00:01 bone 2343 #> 4687 0.3 4 1944 1944-04-01 12:00:00 blood 2344 #> 4688 0.3 4 1944 1944-04-01 12:00:00 bone 2344 #> 4689 2.5 5 1944 1944-05-02 00:00:01 blood 2345 #> 4690 2.5 5 1944 1944-05-02 00:00:01 bone 2345 #> 4691 5.0 6 1944 1944-06-01 12:00:01 blood 2346 #> 4692 5.0 6 1944 1944-06-01 12:00:01 bone 2346 #> 4693 5.0 7 1944 1944-07-02 00:00:00 blood 2347 #> 4694 5.0 7 1944 1944-07-02 00:00:00 bone 2347 #> 4695 16.7 8 1944 1944-08-01 12:00:01 blood 2348 #> 4696 16.7 8 1944 1944-08-01 12:00:01 bone 2348 #> 4697 14.3 9 1944 1944-09-01 00:00:01 blood 2349 #> 4698 14.3 9 1944 1944-09-01 00:00:01 bone 2349 #> 4699 16.9 10 1944 1944-10-01 12:00:00 blood 2350 #> 4700 16.9 10 1944 1944-10-01 12:00:00 bone 2350 #> 4701 10.8 11 1944 1944-11-01 00:00:01 blood 2351 #> 4702 10.8 11 1944 1944-11-01 00:00:01 bone 2351 #> 4703 28.4 12 1944 1944-12-01 12:00:01 blood 2352 #> 4704 28.4 12 1944 1944-12-01 12:00:01 bone 2352 #> 4705 18.5 1 1945 1945-01-01 00:00:00 blood 2353 #> 4706 18.5 1 1945 1945-01-01 00:00:00 bone 2353 #> 4707 12.7 2 1945 1945-01-31 10:00:01 blood 2354 #> 4708 12.7 2 1945 1945-01-31 10:00:01 bone 2354 #> 4709 21.5 3 1945 1945-03-02 20:00:01 blood 2355 #> 4710 21.5 3 1945 1945-03-02 20:00:01 bone 2355 #> 4711 32.0 4 1945 1945-04-02 06:00:00 blood 2356 #> 4712 32.0 4 1945 1945-04-02 06:00:00 bone 2356 #> 4713 30.6 5 1945 1945-05-02 16:00:01 blood 2357 #> 4714 30.6 5 1945 1945-05-02 16:00:01 bone 2357 #> 4715 36.2 6 1945 1945-06-02 02:00:01 blood 2358 #> 4716 36.2 6 1945 1945-06-02 02:00:01 bone 2358 #> 4717 42.6 7 1945 1945-07-02 12:00:00 blood 2359 #> 4718 42.6 7 1945 1945-07-02 12:00:00 bone 2359 #> 4719 25.9 8 1945 1945-08-01 22:00:01 blood 2360 #> 4720 25.9 8 1945 1945-08-01 22:00:01 bone 2360 #> 4721 34.9 9 1945 1945-09-01 08:00:01 blood 2361 #> 4722 34.9 9 1945 1945-09-01 08:00:01 bone 2361 #> 4723 68.8 10 1945 1945-10-01 18:00:00 blood 2362 #> 4724 68.8 10 1945 1945-10-01 18:00:00 bone 2362 #> 4725 46.0 11 1945 1945-11-01 04:00:01 blood 2363 #> 4726 46.0 11 1945 1945-11-01 04:00:01 bone 2363 #> 4727 27.4 12 1945 1945-12-01 14:00:01 blood 2364 #> 4728 27.4 12 1945 1945-12-01 14:00:01 bone 2364 #> 4729 47.6 1 1946 1946-01-01 00:00:00 blood 2365 #> 4730 47.6 1 1946 1946-01-01 00:00:00 bone 2365 #> 4731 86.2 2 1946 1946-01-31 10:00:01 blood 2366 #> 4732 86.2 2 1946 1946-01-31 10:00:01 bone 2366 #> 4733 76.6 3 1946 1946-03-02 20:00:01 blood 2367 #> 4734 76.6 3 1946 1946-03-02 20:00:01 bone 2367 #> 4735 75.7 4 1946 1946-04-02 06:00:00 blood 2368 #> 4736 75.7 4 1946 1946-04-02 06:00:00 bone 2368 #> 4737 84.9 5 1946 1946-05-02 16:00:01 blood 2369 #> 4738 84.9 5 1946 1946-05-02 16:00:01 bone 2369 #> 4739 73.5 6 1946 1946-06-02 02:00:01 blood 2370 #> 4740 73.5 6 1946 1946-06-02 02:00:01 bone 2370 #> 4741 116.2 7 1946 1946-07-02 12:00:00 blood 2371 #> 4742 116.2 7 1946 1946-07-02 12:00:00 bone 2371 #> 4743 107.2 8 1946 1946-08-01 22:00:01 blood 2372 #> 4744 107.2 8 1946 1946-08-01 22:00:01 bone 2372 #> 4745 94.4 9 1946 1946-09-01 08:00:01 blood 2373 #> 4746 94.4 9 1946 1946-09-01 08:00:01 bone 2373 #> 4747 102.3 10 1946 1946-10-01 18:00:00 blood 2374 #> 4748 102.3 10 1946 1946-10-01 18:00:00 bone 2374 #> 4749 123.8 11 1946 1946-11-01 04:00:01 blood 2375 #> 4750 123.8 11 1946 1946-11-01 04:00:01 bone 2375 #> 4751 121.7 12 1946 1946-12-01 14:00:01 blood 2376 #> 4752 121.7 12 1946 1946-12-01 14:00:01 bone 2376 #> 4753 115.7 1 1947 1947-01-01 00:00:00 blood 2377 #> 4754 115.7 1 1947 1947-01-01 00:00:00 bone 2377 #> 4755 113.4 2 1947 1947-01-31 10:00:01 blood 2378 #> 4756 113.4 2 1947 1947-01-31 10:00:01 bone 2378 #> 4757 129.8 3 1947 1947-03-02 20:00:01 blood 2379 #> 4758 129.8 3 1947 1947-03-02 20:00:01 bone 2379 #> 4759 149.8 4 1947 1947-04-02 06:00:00 blood 2380 #> 4760 149.8 4 1947 1947-04-02 06:00:00 bone 2380 #> 4761 201.3 5 1947 1947-05-02 16:00:01 blood 2381 #> 4762 201.3 5 1947 1947-05-02 16:00:01 bone 2381 #> 4763 163.9 6 1947 1947-06-02 02:00:01 blood 2382 #> 4764 163.9 6 1947 1947-06-02 02:00:01 bone 2382 #> 4765 157.9 7 1947 1947-07-02 12:00:00 blood 2383 #> 4766 157.9 7 1947 1947-07-02 12:00:00 bone 2383 #> 4767 188.8 8 1947 1947-08-01 22:00:01 blood 2384 #> 4768 188.8 8 1947 1947-08-01 22:00:01 bone 2384 #> 4769 169.4 9 1947 1947-09-01 08:00:01 blood 2385 #> 4770 169.4 9 1947 1947-09-01 08:00:01 bone 2385 #> 4771 163.6 10 1947 1947-10-01 18:00:00 blood 2386 #> 4772 163.6 10 1947 1947-10-01 18:00:00 bone 2386 #> 4773 128.0 11 1947 1947-11-01 04:00:01 blood 2387 #> 4774 128.0 11 1947 1947-11-01 04:00:01 bone 2387 #> 4775 116.5 12 1947 1947-12-01 14:00:01 blood 2388 #> 4776 116.5 12 1947 1947-12-01 14:00:01 bone 2388 #> 4777 108.5 1 1948 1948-01-01 00:00:00 blood 2389 #> 4778 108.5 1 1948 1948-01-01 00:00:00 bone 2389 #> 4779 86.1 2 1948 1948-01-31 12:00:01 blood 2390 #> 4780 86.1 2 1948 1948-01-31 12:00:01 bone 2390 #> 4781 94.8 3 1948 1948-03-02 00:00:01 blood 2391 #> 4782 94.8 3 1948 1948-03-02 00:00:01 bone 2391 #> 4783 189.7 4 1948 1948-04-01 12:00:00 blood 2392 #> 4784 189.7 4 1948 1948-04-01 12:00:00 bone 2392 #> 4785 174.0 5 1948 1948-05-02 00:00:01 blood 2393 #> 4786 174.0 5 1948 1948-05-02 00:00:01 bone 2393 #> 4787 167.8 6 1948 1948-06-01 12:00:01 blood 2394 #> 4788 167.8 6 1948 1948-06-01 12:00:01 bone 2394 #> 4789 142.2 7 1948 1948-07-02 00:00:00 blood 2395 #> 4790 142.2 7 1948 1948-07-02 00:00:00 bone 2395 #> 4791 157.9 8 1948 1948-08-01 12:00:01 blood 2396 #> 4792 157.9 8 1948 1948-08-01 12:00:01 bone 2396 #> 4793 143.3 9 1948 1948-09-01 00:00:01 blood 2397 #> 4794 143.3 9 1948 1948-09-01 00:00:01 bone 2397 #> #> $data_test #> y season year date series time #> 1 136.3 10 1948 1948-10-01 12:00:00 blood 2398 #> 2 136.3 10 1948 1948-10-01 12:00:00 bone 2398 #> 3 95.8 11 1948 1948-11-01 00:00:01 blood 2399 #> 4 95.8 11 1948 1948-11-01 00:00:01 bone 2399 #> 5 138.0 12 1948 1948-12-01 12:00:01 blood 2400 #> 6 138.0 12 1948 1948-12-01 12:00:01 bone 2400 #> 7 119.1 1 1949 1949-01-01 00:00:00 blood 2401 #> 8 119.1 1 1949 1949-01-01 00:00:00 bone 2401 #> 9 182.3 2 1949 1949-01-31 10:00:01 blood 2402 #> 10 182.3 2 1949 1949-01-31 10:00:01 bone 2402 #> 11 157.5 3 1949 1949-03-02 20:00:01 blood 2403 #> 12 157.5 3 1949 1949-03-02 20:00:01 bone 2403 #> 13 147.0 4 1949 1949-04-02 06:00:00 blood 2404 #> 14 147.0 4 1949 1949-04-02 06:00:00 bone 2404 #> 15 106.2 5 1949 1949-05-02 16:00:01 blood 2405 #> 16 106.2 5 1949 1949-05-02 16:00:01 bone 2405 #> 17 121.7 6 1949 1949-06-02 02:00:01 blood 2406 #> 18 121.7 6 1949 1949-06-02 02:00:01 bone 2406 #> 19 125.8 7 1949 1949-07-02 12:00:00 blood 2407 #> 20 125.8 7 1949 1949-07-02 12:00:00 bone 2407 #> 21 123.8 8 1949 1949-08-01 22:00:01 blood 2408 #> 22 123.8 8 1949 1949-08-01 22:00:01 bone 2408 #> 23 145.3 9 1949 1949-09-01 08:00:01 blood 2409 #> 24 145.3 9 1949 1949-09-01 08:00:01 bone 2409 #> 25 131.6 10 1949 1949-10-01 18:00:00 blood 2410 #> 26 131.6 10 1949 1949-10-01 18:00:00 bone 2410 #> 27 143.5 11 1949 1949-11-01 04:00:01 blood 2411 #> 28 143.5 11 1949 1949-11-01 04:00:01 bone 2411 #> 29 117.6 12 1949 1949-12-01 14:00:01 blood 2412 #> 30 117.6 12 1949 1949-12-01 14:00:01 bone 2412 #> 31 101.6 1 1950 1950-01-01 00:00:00 blood 2413 #> 32 101.6 1 1950 1950-01-01 00:00:00 bone 2413 #> 33 94.8 2 1950 1950-01-31 10:00:01 blood 2414 #> 34 94.8 2 1950 1950-01-31 10:00:01 bone 2414 #> 35 109.7 3 1950 1950-03-02 20:00:01 blood 2415 #> 36 109.7 3 1950 1950-03-02 20:00:01 bone 2415 #> 37 113.4 4 1950 1950-04-02 06:00:00 blood 2416 #> 38 113.4 4 1950 1950-04-02 06:00:00 bone 2416 #> 39 106.2 5 1950 1950-05-02 16:00:01 blood 2417 #> 40 106.2 5 1950 1950-05-02 16:00:01 bone 2417 #> 41 83.6 6 1950 1950-06-02 02:00:01 blood 2418 #> 42 83.6 6 1950 1950-06-02 02:00:01 bone 2418 #> 43 91.0 7 1950 1950-07-02 12:00:00 blood 2419 #> 44 91.0 7 1950 1950-07-02 12:00:00 bone 2419 #> 45 85.2 8 1950 1950-08-01 22:00:01 blood 2420 #> 46 85.2 8 1950 1950-08-01 22:00:01 bone 2420 #> 47 51.3 9 1950 1950-09-01 08:00:01 blood 2421 #> 48 51.3 9 1950 1950-09-01 08:00:01 bone 2421 #> 49 61.4 10 1950 1950-10-01 18:00:00 blood 2422 #> 50 61.4 10 1950 1950-10-01 18:00:00 bone 2422 #> 51 54.8 11 1950 1950-11-01 04:00:01 blood 2423 #> 52 54.8 11 1950 1950-11-01 04:00:01 bone 2423 #> 53 54.1 12 1950 1950-12-01 14:00:01 blood 2424 #> 54 54.1 12 1950 1950-12-01 14:00:01 bone 2424 #> 55 59.9 1 1951 1951-01-01 00:00:00 blood 2425 #> 56 59.9 1 1951 1951-01-01 00:00:00 bone 2425 #> 57 59.9 2 1951 1951-01-31 10:00:01 blood 2426 #> 58 59.9 2 1951 1951-01-31 10:00:01 bone 2426 #> 59 59.9 3 1951 1951-03-02 20:00:01 blood 2427 #> 60 59.9 3 1951 1951-03-02 20:00:01 bone 2427 #> 61 92.9 4 1951 1951-04-02 06:00:00 blood 2428 #> 62 92.9 4 1951 1951-04-02 06:00:00 bone 2428 #> 63 108.5 5 1951 1951-05-02 16:00:01 blood 2429 #> 64 108.5 5 1951 1951-05-02 16:00:01 bone 2429 #> 65 100.6 6 1951 1951-06-02 02:00:01 blood 2430 #> 66 100.6 6 1951 1951-06-02 02:00:01 bone 2430 #> 67 61.5 7 1951 1951-07-02 12:00:00 blood 2431 #> 68 61.5 7 1951 1951-07-02 12:00:00 bone 2431 #> 69 61.0 8 1951 1951-08-01 22:00:01 blood 2432 #> 70 61.0 8 1951 1951-08-01 22:00:01 bone 2432 #> 71 83.1 9 1951 1951-09-01 08:00:01 blood 2433 #> 72 83.1 9 1951 1951-09-01 08:00:01 bone 2433 #> 73 51.6 10 1951 1951-10-01 18:00:00 blood 2434 #> 74 51.6 10 1951 1951-10-01 18:00:00 bone 2434 #> 75 52.4 11 1951 1951-11-01 04:00:01 blood 2435 #> 76 52.4 11 1951 1951-11-01 04:00:01 bone 2435 #> 77 45.8 12 1951 1951-12-01 14:00:01 blood 2436 #> 78 45.8 12 1951 1951-12-01 14:00:01 bone 2436 #> 79 40.7 1 1952 1952-01-01 00:00:00 blood 2437 #> 80 40.7 1 1952 1952-01-01 00:00:00 bone 2437 #> 81 22.7 2 1952 1952-01-31 12:00:01 blood 2438 #> 82 22.7 2 1952 1952-01-31 12:00:01 bone 2438 #> 83 22.0 3 1952 1952-03-02 00:00:01 blood 2439 #> 84 22.0 3 1952 1952-03-02 00:00:01 bone 2439 #> 85 29.1 4 1952 1952-04-01 12:00:00 blood 2440 #> 86 29.1 4 1952 1952-04-01 12:00:00 bone 2440 #> 87 23.4 5 1952 1952-05-02 00:00:01 blood 2441 #> 88 23.4 5 1952 1952-05-02 00:00:01 bone 2441 #> 89 36.4 6 1952 1952-06-01 12:00:01 blood 2442 #> 90 36.4 6 1952 1952-06-01 12:00:01 bone 2442 #> 91 39.3 7 1952 1952-07-02 00:00:00 blood 2443 #> 92 39.3 7 1952 1952-07-02 00:00:00 bone 2443 #> 93 54.9 8 1952 1952-08-01 12:00:01 blood 2444 #> 94 54.9 8 1952 1952-08-01 12:00:01 bone 2444 #> 95 28.2 9 1952 1952-09-01 00:00:01 blood 2445 #> 96 28.2 9 1952 1952-09-01 00:00:01 bone 2445 #> 97 23.8 10 1952 1952-10-01 12:00:00 blood 2446 #> 98 23.8 10 1952 1952-10-01 12:00:00 bone 2446 #> 99 22.1 11 1952 1952-11-01 00:00:01 blood 2447 #> 100 22.1 11 1952 1952-11-01 00:00:01 bone 2447 #> 101 34.3 12 1952 1952-12-01 12:00:01 blood 2448 #> 102 34.3 12 1952 1952-12-01 12:00:01 bone 2448 #> 103 26.5 1 1953 1953-01-01 00:00:00 blood 2449 #> 104 26.5 1 1953 1953-01-01 00:00:00 bone 2449 #> 105 3.9 2 1953 1953-01-31 10:00:01 blood 2450 #> 106 3.9 2 1953 1953-01-31 10:00:01 bone 2450 #> 107 10.0 3 1953 1953-03-02 20:00:01 blood 2451 #> 108 10.0 3 1953 1953-03-02 20:00:01 bone 2451 #> 109 27.8 4 1953 1953-04-02 06:00:00 blood 2452 #> 110 27.8 4 1953 1953-04-02 06:00:00 bone 2452 #> 111 12.5 5 1953 1953-05-02 16:00:01 blood 2453 #> 112 12.5 5 1953 1953-05-02 16:00:01 bone 2453 #> 113 21.8 6 1953 1953-06-02 02:00:01 blood 2454 #> 114 21.8 6 1953 1953-06-02 02:00:01 bone 2454 #> 115 8.6 7 1953 1953-07-02 12:00:00 blood 2455 #> 116 8.6 7 1953 1953-07-02 12:00:00 bone 2455 #> 117 23.5 8 1953 1953-08-01 22:00:01 blood 2456 #> 118 23.5 8 1953 1953-08-01 22:00:01 bone 2456 #> 119 19.3 9 1953 1953-09-01 08:00:01 blood 2457 #> 120 19.3 9 1953 1953-09-01 08:00:01 bone 2457 #> 121 8.2 10 1953 1953-10-01 18:00:00 blood 2458 #> 122 8.2 10 1953 1953-10-01 18:00:00 bone 2458 #> 123 1.6 11 1953 1953-11-01 04:00:01 blood 2459 #> 124 1.6 11 1953 1953-11-01 04:00:01 bone 2459 #> 125 2.5 12 1953 1953-12-01 14:00:01 blood 2460 #> 126 2.5 12 1953 1953-12-01 14:00:01 bone 2460 #> 127 0.2 1 1954 1954-01-01 00:00:00 blood 2461 #> 128 0.2 1 1954 1954-01-01 00:00:00 bone 2461 #> 129 0.5 2 1954 1954-01-31 10:00:01 blood 2462 #> 130 0.5 2 1954 1954-01-31 10:00:01 bone 2462 #> 131 10.9 3 1954 1954-03-02 20:00:01 blood 2463 #> 132 10.9 3 1954 1954-03-02 20:00:01 bone 2463 #> 133 1.8 4 1954 1954-04-02 06:00:00 blood 2464 #> 134 1.8 4 1954 1954-04-02 06:00:00 bone 2464 #> 135 0.8 5 1954 1954-05-02 16:00:01 blood 2465 #> 136 0.8 5 1954 1954-05-02 16:00:01 bone 2465 #> 137 0.2 6 1954 1954-06-02 02:00:01 blood 2466 #> 138 0.2 6 1954 1954-06-02 02:00:01 bone 2466 #> 139 4.8 7 1954 1954-07-02 12:00:00 blood 2467 #> 140 4.8 7 1954 1954-07-02 12:00:00 bone 2467 #> 141 8.4 8 1954 1954-08-01 22:00:01 blood 2468 #> 142 8.4 8 1954 1954-08-01 22:00:01 bone 2468 #> 143 1.5 9 1954 1954-09-01 08:00:01 blood 2469 #> 144 1.5 9 1954 1954-09-01 08:00:01 bone 2469 #> 145 7.0 10 1954 1954-10-01 18:00:00 blood 2470 #> 146 7.0 10 1954 1954-10-01 18:00:00 bone 2470 #> 147 9.2 11 1954 1954-11-01 04:00:01 blood 2471 #> 148 9.2 11 1954 1954-11-01 04:00:01 bone 2471 #> 149 7.6 12 1954 1954-12-01 14:00:01 blood 2472 #> 150 7.6 12 1954 1954-12-01 14:00:01 bone 2472 #> 151 23.1 1 1955 1955-01-01 00:00:00 blood 2473 #> 152 23.1 1 1955 1955-01-01 00:00:00 bone 2473 #> 153 20.8 2 1955 1955-01-31 10:00:01 blood 2474 #> 154 20.8 2 1955 1955-01-31 10:00:01 bone 2474 #> 155 4.9 3 1955 1955-03-02 20:00:01 blood 2475 #> 156 4.9 3 1955 1955-03-02 20:00:01 bone 2475 #> 157 11.3 4 1955 1955-04-02 06:00:00 blood 2476 #> 158 11.3 4 1955 1955-04-02 06:00:00 bone 2476 #> 159 28.9 5 1955 1955-05-02 16:00:01 blood 2477 #> 160 28.9 5 1955 1955-05-02 16:00:01 bone 2477 #> 161 31.7 6 1955 1955-06-02 02:00:01 blood 2478 #> 162 31.7 6 1955 1955-06-02 02:00:01 bone 2478 #> 163 26.7 7 1955 1955-07-02 12:00:00 blood 2479 #> 164 26.7 7 1955 1955-07-02 12:00:00 bone 2479 #> 165 40.7 8 1955 1955-08-01 22:00:01 blood 2480 #> 166 40.7 8 1955 1955-08-01 22:00:01 bone 2480 #> 167 42.7 9 1955 1955-09-01 08:00:01 blood 2481 #> 168 42.7 9 1955 1955-09-01 08:00:01 bone 2481 #> 169 58.5 10 1955 1955-10-01 18:00:00 blood 2482 #> 170 58.5 10 1955 1955-10-01 18:00:00 bone 2482 #> 171 89.2 11 1955 1955-11-01 04:00:01 blood 2483 #> 172 89.2 11 1955 1955-11-01 04:00:01 bone 2483 #> 173 76.9 12 1955 1955-12-01 14:00:01 blood 2484 #> 174 76.9 12 1955 1955-12-01 14:00:01 bone 2484 #> 175 73.6 1 1956 1956-01-01 00:00:00 blood 2485 #> 176 73.6 1 1956 1956-01-01 00:00:00 bone 2485 #> 177 124.0 2 1956 1956-01-31 12:00:01 blood 2486 #> 178 124.0 2 1956 1956-01-31 12:00:01 bone 2486 #> 179 118.4 3 1956 1956-03-02 00:00:01 blood 2487 #> 180 118.4 3 1956 1956-03-02 00:00:01 bone 2487 #> 181 110.7 4 1956 1956-04-01 12:00:00 blood 2488 #> 182 110.7 4 1956 1956-04-01 12:00:00 bone 2488 #> 183 136.6 5 1956 1956-05-02 00:00:01 blood 2489 #> 184 136.6 5 1956 1956-05-02 00:00:01 bone 2489 #> 185 116.6 6 1956 1956-06-01 12:00:01 blood 2490 #> 186 116.6 6 1956 1956-06-01 12:00:01 bone 2490 #> 187 129.1 7 1956 1956-07-02 00:00:00 blood 2491 #> 188 129.1 7 1956 1956-07-02 00:00:00 bone 2491 #> 189 169.6 8 1956 1956-08-01 12:00:01 blood 2492 #> 190 169.6 8 1956 1956-08-01 12:00:01 bone 2492 #> 191 173.2 9 1956 1956-09-01 00:00:01 blood 2493 #> 192 173.2 9 1956 1956-09-01 00:00:01 bone 2493 #> 193 155.3 10 1956 1956-10-01 12:00:00 blood 2494 #> 194 155.3 10 1956 1956-10-01 12:00:00 bone 2494 #> 195 201.3 11 1956 1956-11-01 00:00:01 blood 2495 #> 196 201.3 11 1956 1956-11-01 00:00:01 bone 2495 #> 197 192.1 12 1956 1956-12-01 12:00:01 blood 2496 #> 198 192.1 12 1956 1956-12-01 12:00:01 bone 2496 #> 199 165.0 1 1957 1957-01-01 00:00:00 blood 2497 #> 200 165.0 1 1957 1957-01-01 00:00:00 bone 2497 #> 201 130.2 2 1957 1957-01-31 10:00:01 blood 2498 #> 202 130.2 2 1957 1957-01-31 10:00:01 bone 2498 #> 203 157.4 3 1957 1957-03-02 20:00:01 blood 2499 #> 204 157.4 3 1957 1957-03-02 20:00:01 bone 2499 #> 205 175.2 4 1957 1957-04-02 06:00:00 blood 2500 #> 206 175.2 4 1957 1957-04-02 06:00:00 bone 2500 #> 207 164.6 5 1957 1957-05-02 16:00:01 blood 2501 #> 208 164.6 5 1957 1957-05-02 16:00:01 bone 2501 #> 209 200.7 6 1957 1957-06-02 02:00:01 blood 2502 #> 210 200.7 6 1957 1957-06-02 02:00:01 bone 2502 #> 211 187.2 7 1957 1957-07-02 12:00:00 blood 2503 #> 212 187.2 7 1957 1957-07-02 12:00:00 bone 2503 #> 213 158.0 8 1957 1957-08-01 22:00:01 blood 2504 #> 214 158.0 8 1957 1957-08-01 22:00:01 bone 2504 #> 215 235.8 9 1957 1957-09-01 08:00:01 blood 2505 #> 216 235.8 9 1957 1957-09-01 08:00:01 bone 2505 #> 217 253.8 10 1957 1957-10-01 18:00:00 blood 2506 #> 218 253.8 10 1957 1957-10-01 18:00:00 bone 2506 #> 219 210.9 11 1957 1957-11-01 04:00:01 blood 2507 #> 220 210.9 11 1957 1957-11-01 04:00:01 bone 2507 #> 221 239.4 12 1957 1957-12-01 14:00:01 blood 2508 #> 222 239.4 12 1957 1957-12-01 14:00:01 bone 2508 #> 223 202.5 1 1958 1958-01-01 00:00:00 blood 2509 #> 224 202.5 1 1958 1958-01-01 00:00:00 bone 2509 #> 225 164.9 2 1958 1958-01-31 10:00:01 blood 2510 #> 226 164.9 2 1958 1958-01-31 10:00:01 bone 2510 #> 227 190.7 3 1958 1958-03-02 20:00:01 blood 2511 #> 228 190.7 3 1958 1958-03-02 20:00:01 bone 2511 #> 229 196.0 4 1958 1958-04-02 06:00:00 blood 2512 #> 230 196.0 4 1958 1958-04-02 06:00:00 bone 2512 #> 231 175.3 5 1958 1958-05-02 16:00:01 blood 2513 #> 232 175.3 5 1958 1958-05-02 16:00:01 bone 2513 #> 233 171.5 6 1958 1958-06-02 02:00:01 blood 2514 #> 234 171.5 6 1958 1958-06-02 02:00:01 bone 2514 #> 235 191.4 7 1958 1958-07-02 12:00:00 blood 2515 #> 236 191.4 7 1958 1958-07-02 12:00:00 bone 2515 #> 237 200.2 8 1958 1958-08-01 22:00:01 blood 2516 #> 238 200.2 8 1958 1958-08-01 22:00:01 bone 2516 #> 239 201.2 9 1958 1958-09-01 08:00:01 blood 2517 #> 240 201.2 9 1958 1958-09-01 08:00:01 bone 2517 #> 241 181.5 10 1958 1958-10-01 18:00:00 blood 2518 #> 242 181.5 10 1958 1958-10-01 18:00:00 bone 2518 #> 243 152.3 11 1958 1958-11-01 04:00:01 blood 2519 #> 244 152.3 11 1958 1958-11-01 04:00:01 bone 2519 #> 245 187.6 12 1958 1958-12-01 14:00:01 blood 2520 #> 246 187.6 12 1958 1958-12-01 14:00:01 bone 2520 #> 247 217.4 1 1959 1959-01-01 00:00:00 blood 2521 #> 248 217.4 1 1959 1959-01-01 00:00:00 bone 2521 #> 249 143.1 2 1959 1959-01-31 10:00:01 blood 2522 #> 250 143.1 2 1959 1959-01-31 10:00:01 bone 2522 #> 251 185.7 3 1959 1959-03-02 20:00:01 blood 2523 #> 252 185.7 3 1959 1959-03-02 20:00:01 bone 2523 #> 253 163.3 4 1959 1959-04-02 06:00:00 blood 2524 #> 254 163.3 4 1959 1959-04-02 06:00:00 bone 2524 #> 255 172.0 5 1959 1959-05-02 16:00:01 blood 2525 #> 256 172.0 5 1959 1959-05-02 16:00:01 bone 2525 #> 257 168.7 6 1959 1959-06-02 02:00:01 blood 2526 #> 258 168.7 6 1959 1959-06-02 02:00:01 bone 2526 #> 259 149.6 7 1959 1959-07-02 12:00:00 blood 2527 #> 260 149.6 7 1959 1959-07-02 12:00:00 bone 2527 #> 261 199.6 8 1959 1959-08-01 22:00:01 blood 2528 #> 262 199.6 8 1959 1959-08-01 22:00:01 bone 2528 #> 263 145.2 9 1959 1959-09-01 08:00:01 blood 2529 #> 264 145.2 9 1959 1959-09-01 08:00:01 bone 2529 #> 265 111.4 10 1959 1959-10-01 18:00:00 blood 2530 #> 266 111.4 10 1959 1959-10-01 18:00:00 bone 2530 #> 267 124.0 11 1959 1959-11-01 04:00:01 blood 2531 #> 268 124.0 11 1959 1959-11-01 04:00:01 bone 2531 #> 269 125.0 12 1959 1959-12-01 14:00:01 blood 2532 #> 270 125.0 12 1959 1959-12-01 14:00:01 bone 2532 #> 271 146.3 1 1960 1960-01-01 00:00:00 blood 2533 #> 272 146.3 1 1960 1960-01-01 00:00:00 bone 2533 #> 273 106.0 2 1960 1960-01-31 12:00:01 blood 2534 #> 274 106.0 2 1960 1960-01-31 12:00:01 bone 2534 #> 275 102.2 3 1960 1960-03-02 00:00:01 blood 2535 #> 276 102.2 3 1960 1960-03-02 00:00:01 bone 2535 #> 277 122.0 4 1960 1960-04-01 12:00:00 blood 2536 #> 278 122.0 4 1960 1960-04-01 12:00:00 bone 2536 #> 279 119.6 5 1960 1960-05-02 00:00:01 blood 2537 #> 280 119.6 5 1960 1960-05-02 00:00:01 bone 2537 #> 281 110.2 6 1960 1960-06-01 12:00:01 blood 2538 #> 282 110.2 6 1960 1960-06-01 12:00:01 bone 2538 #> 283 121.7 7 1960 1960-07-02 00:00:00 blood 2539 #> 284 121.7 7 1960 1960-07-02 00:00:00 bone 2539 #> 285 134.1 8 1960 1960-08-01 12:00:01 blood 2540 #> 286 134.1 8 1960 1960-08-01 12:00:01 bone 2540 #> 287 127.2 9 1960 1960-09-01 00:00:01 blood 2541 #> 288 127.2 9 1960 1960-09-01 00:00:01 bone 2541 #> 289 82.8 10 1960 1960-10-01 12:00:00 blood 2542 #> 290 82.8 10 1960 1960-10-01 12:00:00 bone 2542 #> 291 89.6 11 1960 1960-11-01 00:00:01 blood 2543 #> 292 89.6 11 1960 1960-11-01 00:00:01 bone 2543 #> 293 85.6 12 1960 1960-12-01 12:00:01 blood 2544 #> 294 85.6 12 1960 1960-12-01 12:00:01 bone 2544 #> 295 57.9 1 1961 1961-01-01 00:00:00 blood 2545 #> 296 57.9 1 1961 1961-01-01 00:00:00 bone 2545 #> 297 46.1 2 1961 1961-01-31 10:00:01 blood 2546 #> 298 46.1 2 1961 1961-01-31 10:00:01 bone 2546 #> 299 53.0 3 1961 1961-03-02 20:00:01 blood 2547 #> 300 53.0 3 1961 1961-03-02 20:00:01 bone 2547 #> 301 61.4 4 1961 1961-04-02 06:00:00 blood 2548 #> 302 61.4 4 1961 1961-04-02 06:00:00 bone 2548 #> 303 51.0 5 1961 1961-05-02 16:00:01 blood 2549 #> 304 51.0 5 1961 1961-05-02 16:00:01 bone 2549 #> 305 77.4 6 1961 1961-06-02 02:00:01 blood 2550 #> 306 77.4 6 1961 1961-06-02 02:00:01 bone 2550 #> 307 70.2 7 1961 1961-07-02 12:00:00 blood 2551 #> 308 70.2 7 1961 1961-07-02 12:00:00 bone 2551 #> 309 55.9 8 1961 1961-08-01 22:00:01 blood 2552 #> 310 55.9 8 1961 1961-08-01 22:00:01 bone 2552 #> 311 63.6 9 1961 1961-09-01 08:00:01 blood 2553 #> 312 63.6 9 1961 1961-09-01 08:00:01 bone 2553 #> 313 37.7 10 1961 1961-10-01 18:00:00 blood 2554 #> 314 37.7 10 1961 1961-10-01 18:00:00 bone 2554 #> 315 32.6 11 1961 1961-11-01 04:00:01 blood 2555 #> 316 32.6 11 1961 1961-11-01 04:00:01 bone 2555 #> 317 40.0 12 1961 1961-12-01 14:00:01 blood 2556 #> 318 40.0 12 1961 1961-12-01 14:00:01 bone 2556 #> 319 38.7 1 1962 1962-01-01 00:00:00 blood 2557 #> 320 38.7 1 1962 1962-01-01 00:00:00 bone 2557 #> 321 50.3 2 1962 1962-01-31 10:00:01 blood 2558 #> 322 50.3 2 1962 1962-01-31 10:00:01 bone 2558 #> 323 45.6 3 1962 1962-03-02 20:00:01 blood 2559 #> 324 45.6 3 1962 1962-03-02 20:00:01 bone 2559 #> 325 46.4 4 1962 1962-04-02 06:00:00 blood 2560 #> 326 46.4 4 1962 1962-04-02 06:00:00 bone 2560 #> 327 43.7 5 1962 1962-05-02 16:00:01 blood 2561 #> 328 43.7 5 1962 1962-05-02 16:00:01 bone 2561 #> 329 42.0 6 1962 1962-06-02 02:00:01 blood 2562 #> 330 42.0 6 1962 1962-06-02 02:00:01 bone 2562 #> 331 21.8 7 1962 1962-07-02 12:00:00 blood 2563 #> 332 21.8 7 1962 1962-07-02 12:00:00 bone 2563 #> 333 21.8 8 1962 1962-08-01 22:00:01 blood 2564 #> 334 21.8 8 1962 1962-08-01 22:00:01 bone 2564 #> 335 51.3 9 1962 1962-09-01 08:00:01 blood 2565 #> 336 51.3 9 1962 1962-09-01 08:00:01 bone 2565 #> 337 39.5 10 1962 1962-10-01 18:00:00 blood 2566 #> 338 39.5 10 1962 1962-10-01 18:00:00 bone 2566 #> 339 26.9 11 1962 1962-11-01 04:00:01 blood 2567 #> 340 26.9 11 1962 1962-11-01 04:00:01 bone 2567 #> 341 23.2 12 1962 1962-12-01 14:00:01 blood 2568 #> 342 23.2 12 1962 1962-12-01 14:00:01 bone 2568 #> 343 19.8 1 1963 1963-01-01 00:00:00 blood 2569 #> 344 19.8 1 1963 1963-01-01 00:00:00 bone 2569 #> 345 24.4 2 1963 1963-01-31 10:00:01 blood 2570 #> 346 24.4 2 1963 1963-01-31 10:00:01 bone 2570 #> 347 17.1 3 1963 1963-03-02 20:00:01 blood 2571 #> 348 17.1 3 1963 1963-03-02 20:00:01 bone 2571 #> 349 29.3 4 1963 1963-04-02 06:00:00 blood 2572 #> 350 29.3 4 1963 1963-04-02 06:00:00 bone 2572 #> 351 43.0 5 1963 1963-05-02 16:00:01 blood 2573 #> 352 43.0 5 1963 1963-05-02 16:00:01 bone 2573 #> 353 35.9 6 1963 1963-06-02 02:00:01 blood 2574 #> 354 35.9 6 1963 1963-06-02 02:00:01 bone 2574 #> 355 19.6 7 1963 1963-07-02 12:00:00 blood 2575 #> 356 19.6 7 1963 1963-07-02 12:00:00 bone 2575 #> 357 33.2 8 1963 1963-08-01 22:00:01 blood 2576 #> 358 33.2 8 1963 1963-08-01 22:00:01 bone 2576 #> 359 38.8 9 1963 1963-09-01 08:00:01 blood 2577 #> 360 38.8 9 1963 1963-09-01 08:00:01 bone 2577 #> 361 35.3 10 1963 1963-10-01 18:00:00 blood 2578 #> 362 35.3 10 1963 1963-10-01 18:00:00 bone 2578 #> 363 23.4 11 1963 1963-11-01 04:00:01 blood 2579 #> 364 23.4 11 1963 1963-11-01 04:00:01 bone 2579 #> 365 14.9 12 1963 1963-12-01 14:00:01 blood 2580 #> 366 14.9 12 1963 1963-12-01 14:00:01 bone 2580 #> 367 15.3 1 1964 1964-01-01 00:00:00 blood 2581 #> 368 15.3 1 1964 1964-01-01 00:00:00 bone 2581 #> 369 17.7 2 1964 1964-01-31 12:00:01 blood 2582 #> 370 17.7 2 1964 1964-01-31 12:00:01 bone 2582 #> 371 16.5 3 1964 1964-03-02 00:00:01 blood 2583 #> 372 16.5 3 1964 1964-03-02 00:00:01 bone 2583 #> 373 8.6 4 1964 1964-04-01 12:00:00 blood 2584 #> 374 8.6 4 1964 1964-04-01 12:00:00 bone 2584 #> 375 9.5 5 1964 1964-05-02 00:00:01 blood 2585 #> 376 9.5 5 1964 1964-05-02 00:00:01 bone 2585 #> 377 9.1 6 1964 1964-06-01 12:00:01 blood 2586 #> 378 9.1 6 1964 1964-06-01 12:00:01 bone 2586 #> 379 3.1 7 1964 1964-07-02 00:00:00 blood 2587 #> 380 3.1 7 1964 1964-07-02 00:00:00 bone 2587 #> 381 9.3 8 1964 1964-08-01 12:00:01 blood 2588 #> 382 9.3 8 1964 1964-08-01 12:00:01 bone 2588 #> 383 4.7 9 1964 1964-09-01 00:00:01 blood 2589 #> 384 4.7 9 1964 1964-09-01 00:00:01 bone 2589 #> 385 6.1 10 1964 1964-10-01 12:00:00 blood 2590 #> 386 6.1 10 1964 1964-10-01 12:00:00 bone 2590 #> 387 7.4 11 1964 1964-11-01 00:00:01 blood 2591 #> 388 7.4 11 1964 1964-11-01 00:00:01 bone 2591 #> 389 15.1 12 1964 1964-12-01 12:00:01 blood 2592 #> 390 15.1 12 1964 1964-12-01 12:00:01 bone 2592 #> 391 17.5 1 1965 1965-01-01 00:00:00 blood 2593 #> 392 17.5 1 1965 1965-01-01 00:00:00 bone 2593 #> 393 14.2 2 1965 1965-01-31 10:00:01 blood 2594 #> 394 14.2 2 1965 1965-01-31 10:00:01 bone 2594 #> 395 11.7 3 1965 1965-03-02 20:00:01 blood 2595 #> 396 11.7 3 1965 1965-03-02 20:00:01 bone 2595 #> 397 6.8 4 1965 1965-04-02 06:00:00 blood 2596 #> 398 6.8 4 1965 1965-04-02 06:00:00 bone 2596 #> 399 24.1 5 1965 1965-05-02 16:00:01 blood 2597 #> 400 24.1 5 1965 1965-05-02 16:00:01 bone 2597 #> 401 15.9 6 1965 1965-06-02 02:00:01 blood 2598 #> 402 15.9 6 1965 1965-06-02 02:00:01 bone 2598 #> 403 11.9 7 1965 1965-07-02 12:00:00 blood 2599 #> 404 11.9 7 1965 1965-07-02 12:00:00 bone 2599 #> 405 8.9 8 1965 1965-08-01 22:00:01 blood 2600 #> 406 8.9 8 1965 1965-08-01 22:00:01 bone 2600 #> 407 16.8 9 1965 1965-09-01 08:00:01 blood 2601 #> 408 16.8 9 1965 1965-09-01 08:00:01 bone 2601 #> 409 20.1 10 1965 1965-10-01 18:00:00 blood 2602 #> 410 20.1 10 1965 1965-10-01 18:00:00 bone 2602 #> 411 15.8 11 1965 1965-11-01 04:00:01 blood 2603 #> 412 15.8 11 1965 1965-11-01 04:00:01 bone 2603 #> 413 17.0 12 1965 1965-12-01 14:00:01 blood 2604 #> 414 17.0 12 1965 1965-12-01 14:00:01 bone 2604 #> 415 28.2 1 1966 1966-01-01 00:00:00 blood 2605 #> 416 28.2 1 1966 1966-01-01 00:00:00 bone 2605 #> 417 24.4 2 1966 1966-01-31 10:00:01 blood 2606 #> 418 24.4 2 1966 1966-01-31 10:00:01 bone 2606 #> 419 25.3 3 1966 1966-03-02 20:00:01 blood 2607 #> 420 25.3 3 1966 1966-03-02 20:00:01 bone 2607 #> 421 48.7 4 1966 1966-04-02 06:00:00 blood 2608 #> 422 48.7 4 1966 1966-04-02 06:00:00 bone 2608 #> 423 45.3 5 1966 1966-05-02 16:00:01 blood 2609 #> 424 45.3 5 1966 1966-05-02 16:00:01 bone 2609 #> 425 47.7 6 1966 1966-06-02 02:00:01 blood 2610 #> 426 47.7 6 1966 1966-06-02 02:00:01 bone 2610 #> 427 56.7 7 1966 1966-07-02 12:00:00 blood 2611 #> 428 56.7 7 1966 1966-07-02 12:00:00 bone 2611 #> 429 51.2 8 1966 1966-08-01 22:00:01 blood 2612 #> 430 51.2 8 1966 1966-08-01 22:00:01 bone 2612 #> 431 50.2 9 1966 1966-09-01 08:00:01 blood 2613 #> 432 50.2 9 1966 1966-09-01 08:00:01 bone 2613 #> 433 57.2 10 1966 1966-10-01 18:00:00 blood 2614 #> 434 57.2 10 1966 1966-10-01 18:00:00 bone 2614 #> 435 57.2 11 1966 1966-11-01 04:00:01 blood 2615 #> 436 57.2 11 1966 1966-11-01 04:00:01 bone 2615 #> 437 70.4 12 1966 1966-12-01 14:00:01 blood 2616 #> 438 70.4 12 1966 1966-12-01 14:00:01 bone 2616 #> 439 110.9 1 1967 1967-01-01 00:00:00 blood 2617 #> 440 110.9 1 1967 1967-01-01 00:00:00 bone 2617 #> 441 93.6 2 1967 1967-01-31 10:00:01 blood 2618 #> 442 93.6 2 1967 1967-01-31 10:00:01 bone 2618 #> 443 111.8 3 1967 1967-03-02 20:00:01 blood 2619 #> 444 111.8 3 1967 1967-03-02 20:00:01 bone 2619 #> 445 69.5 4 1967 1967-04-02 06:00:00 blood 2620 #> 446 69.5 4 1967 1967-04-02 06:00:00 bone 2620 #> 447 86.5 5 1967 1967-05-02 16:00:01 blood 2621 #> 448 86.5 5 1967 1967-05-02 16:00:01 bone 2621 #> 449 67.3 6 1967 1967-06-02 02:00:01 blood 2622 #> 450 67.3 6 1967 1967-06-02 02:00:01 bone 2622 #> 451 91.5 7 1967 1967-07-02 12:00:00 blood 2623 #> 452 91.5 7 1967 1967-07-02 12:00:00 bone 2623 #> 453 107.2 8 1967 1967-08-01 22:00:01 blood 2624 #> 454 107.2 8 1967 1967-08-01 22:00:01 bone 2624 #> 455 76.8 9 1967 1967-09-01 08:00:01 blood 2625 #> 456 76.8 9 1967 1967-09-01 08:00:01 bone 2625 #> 457 88.2 10 1967 1967-10-01 18:00:00 blood 2626 #> 458 88.2 10 1967 1967-10-01 18:00:00 bone 2626 #> 459 94.3 11 1967 1967-11-01 04:00:01 blood 2627 #> 460 94.3 11 1967 1967-11-01 04:00:01 bone 2627 #> 461 126.4 12 1967 1967-12-01 14:00:01 blood 2628 #> 462 126.4 12 1967 1967-12-01 14:00:01 bone 2628 #> 463 121.8 1 1968 1968-01-01 00:00:00 blood 2629 #> 464 121.8 1 1968 1968-01-01 00:00:00 bone 2629 #> 465 111.9 2 1968 1968-01-31 12:00:01 blood 2630 #> 466 111.9 2 1968 1968-01-31 12:00:01 bone 2630 #> 467 92.2 3 1968 1968-03-02 00:00:01 blood 2631 #> 468 92.2 3 1968 1968-03-02 00:00:01 bone 2631 #> 469 81.2 4 1968 1968-04-01 12:00:00 blood 2632 #> 470 81.2 4 1968 1968-04-01 12:00:00 bone 2632 #> 471 127.2 5 1968 1968-05-02 00:00:01 blood 2633 #> 472 127.2 5 1968 1968-05-02 00:00:01 bone 2633 #> 473 110.3 6 1968 1968-06-01 12:00:01 blood 2634 #> 474 110.3 6 1968 1968-06-01 12:00:01 bone 2634 #> 475 96.1 7 1968 1968-07-02 00:00:00 blood 2635 #> 476 96.1 7 1968 1968-07-02 00:00:00 bone 2635 #> 477 109.3 8 1968 1968-08-01 12:00:01 blood 2636 #> 478 109.3 8 1968 1968-08-01 12:00:01 bone 2636 #> 479 117.2 9 1968 1968-09-01 00:00:01 blood 2637 #> 480 117.2 9 1968 1968-09-01 00:00:01 bone 2637 #> 481 107.7 10 1968 1968-10-01 12:00:00 blood 2638 #> 482 107.7 10 1968 1968-10-01 12:00:00 bone 2638 #> 483 86.0 11 1968 1968-11-01 00:00:01 blood 2639 #> 484 86.0 11 1968 1968-11-01 00:00:01 bone 2639 #> 485 109.8 12 1968 1968-12-01 12:00:01 blood 2640 #> 486 109.8 12 1968 1968-12-01 12:00:01 bone 2640 #> 487 104.4 1 1969 1969-01-01 00:00:00 blood 2641 #> 488 104.4 1 1969 1969-01-01 00:00:00 bone 2641 #> 489 120.5 2 1969 1969-01-31 10:00:01 blood 2642 #> 490 120.5 2 1969 1969-01-31 10:00:01 bone 2642 #> 491 135.8 3 1969 1969-03-02 20:00:01 blood 2643 #> 492 135.8 3 1969 1969-03-02 20:00:01 bone 2643 #> 493 106.8 4 1969 1969-04-02 06:00:00 blood 2644 #> 494 106.8 4 1969 1969-04-02 06:00:00 bone 2644 #> 495 120.0 5 1969 1969-05-02 16:00:01 blood 2645 #> 496 120.0 5 1969 1969-05-02 16:00:01 bone 2645 #> 497 106.0 6 1969 1969-06-02 02:00:01 blood 2646 #> 498 106.0 6 1969 1969-06-02 02:00:01 bone 2646 #> 499 96.8 7 1969 1969-07-02 12:00:00 blood 2647 #> 500 96.8 7 1969 1969-07-02 12:00:00 bone 2647 #> 501 98.0 8 1969 1969-08-01 22:00:01 blood 2648 #> 502 98.0 8 1969 1969-08-01 22:00:01 bone 2648 #> 503 91.3 9 1969 1969-09-01 08:00:01 blood 2649 #> 504 91.3 9 1969 1969-09-01 08:00:01 bone 2649 #> 505 95.7 10 1969 1969-10-01 18:00:00 blood 2650 #> 506 95.7 10 1969 1969-10-01 18:00:00 bone 2650 #> 507 93.5 11 1969 1969-11-01 04:00:01 blood 2651 #> 508 93.5 11 1969 1969-11-01 04:00:01 bone 2651 #> 509 97.9 12 1969 1969-12-01 14:00:01 blood 2652 #> 510 97.9 12 1969 1969-12-01 14:00:01 bone 2652 #> 511 111.5 1 1970 1970-01-01 00:00:00 blood 2653 #> 512 111.5 1 1970 1970-01-01 00:00:00 bone 2653 #> 513 127.8 2 1970 1970-01-31 10:00:00 blood 2654 #> 514 127.8 2 1970 1970-01-31 10:00:00 bone 2654 #> 515 102.9 3 1970 1970-03-02 20:00:00 blood 2655 #> 516 102.9 3 1970 1970-03-02 20:00:00 bone 2655 #> 517 109.5 4 1970 1970-04-02 06:00:00 blood 2656 #> 518 109.5 4 1970 1970-04-02 06:00:00 bone 2656 #> 519 127.5 5 1970 1970-05-02 16:00:00 blood 2657 #> 520 127.5 5 1970 1970-05-02 16:00:00 bone 2657 #> 521 106.8 6 1970 1970-06-02 02:00:00 blood 2658 #> 522 106.8 6 1970 1970-06-02 02:00:00 bone 2658 #> 523 112.5 7 1970 1970-07-02 12:00:00 blood 2659 #> 524 112.5 7 1970 1970-07-02 12:00:00 bone 2659 #> 525 93.0 8 1970 1970-08-01 22:00:00 blood 2660 #> 526 93.0 8 1970 1970-08-01 22:00:00 bone 2660 #> 527 99.5 9 1970 1970-09-01 08:00:00 blood 2661 #> 528 99.5 9 1970 1970-09-01 08:00:00 bone 2661 #> 529 86.6 10 1970 1970-10-01 18:00:00 blood 2662 #> 530 86.6 10 1970 1970-10-01 18:00:00 bone 2662 #> 531 95.2 11 1970 1970-11-01 04:00:00 blood 2663 #> 532 95.2 11 1970 1970-11-01 04:00:00 bone 2663 #> 533 83.5 12 1970 1970-12-01 14:00:00 blood 2664 #> 534 83.5 12 1970 1970-12-01 14:00:00 bone 2664 #> 535 91.3 1 1971 1971-01-01 00:00:00 blood 2665 #> 536 91.3 1 1971 1971-01-01 00:00:00 bone 2665 #> 537 79.0 2 1971 1971-01-31 10:00:00 blood 2666 #> 538 79.0 2 1971 1971-01-31 10:00:00 bone 2666 #> 539 60.7 3 1971 1971-03-02 20:00:00 blood 2667 #> 540 60.7 3 1971 1971-03-02 20:00:00 bone 2667 #> 541 71.8 4 1971 1971-04-02 06:00:00 blood 2668 #> 542 71.8 4 1971 1971-04-02 06:00:00 bone 2668 #> 543 57.5 5 1971 1971-05-02 16:00:00 blood 2669 #> 544 57.5 5 1971 1971-05-02 16:00:00 bone 2669 #> 545 49.8 6 1971 1971-06-02 02:00:00 blood 2670 #> 546 49.8 6 1971 1971-06-02 02:00:00 bone 2670 #> 547 81.0 7 1971 1971-07-02 12:00:00 blood 2671 #> 548 81.0 7 1971 1971-07-02 12:00:00 bone 2671 #> 549 61.4 8 1971 1971-08-01 22:00:00 blood 2672 #> 550 61.4 8 1971 1971-08-01 22:00:00 bone 2672 #> 551 50.2 9 1971 1971-09-01 08:00:00 blood 2673 #> 552 50.2 9 1971 1971-09-01 08:00:00 bone 2673 #> 553 51.7 10 1971 1971-10-01 18:00:00 blood 2674 #> 554 51.7 10 1971 1971-10-01 18:00:00 bone 2674 #> 555 63.2 11 1971 1971-11-01 04:00:00 blood 2675 #> 556 63.2 11 1971 1971-11-01 04:00:00 bone 2675 #> 557 82.2 12 1971 1971-12-01 14:00:00 blood 2676 #> 558 82.2 12 1971 1971-12-01 14:00:00 bone 2676 #> 559 61.5 1 1972 1972-01-01 00:00:00 blood 2677 #> 560 61.5 1 1972 1972-01-01 00:00:00 bone 2677 #> 561 88.4 2 1972 1972-01-31 12:00:00 blood 2678 #> 562 88.4 2 1972 1972-01-31 12:00:00 bone 2678 #> 563 80.1 3 1972 1972-03-02 00:00:00 blood 2679 #> 564 80.1 3 1972 1972-03-02 00:00:00 bone 2679 #> 565 63.2 4 1972 1972-04-01 12:00:00 blood 2680 #> 566 63.2 4 1972 1972-04-01 12:00:00 bone 2680 #> 567 80.5 5 1972 1972-05-02 00:00:00 blood 2681 #> 568 80.5 5 1972 1972-05-02 00:00:00 bone 2681 #> 569 88.0 6 1972 1972-06-01 12:00:00 blood 2682 #> 570 88.0 6 1972 1972-06-01 12:00:00 bone 2682 #> 571 76.5 7 1972 1972-07-02 00:00:00 blood 2683 #> 572 76.5 7 1972 1972-07-02 00:00:00 bone 2683 #> 573 76.8 8 1972 1972-08-01 12:00:00 blood 2684 #> 574 76.8 8 1972 1972-08-01 12:00:00 bone 2684 #> 575 64.0 9 1972 1972-09-01 00:00:00 blood 2685 #> 576 64.0 9 1972 1972-09-01 00:00:00 bone 2685 #> 577 61.3 10 1972 1972-10-01 12:00:00 blood 2686 #> 578 61.3 10 1972 1972-10-01 12:00:00 bone 2686 #> 579 41.6 11 1972 1972-11-01 00:00:00 blood 2687 #> 580 41.6 11 1972 1972-11-01 00:00:00 bone 2687 #> 581 45.3 12 1972 1972-12-01 12:00:00 blood 2688 #> 582 45.3 12 1972 1972-12-01 12:00:00 bone 2688 #> 583 43.4 1 1973 1973-01-01 00:00:00 blood 2689 #> 584 43.4 1 1973 1973-01-01 00:00:00 bone 2689 #> 585 42.9 2 1973 1973-01-31 10:00:00 blood 2690 #> 586 42.9 2 1973 1973-01-31 10:00:00 bone 2690 #> 587 46.0 3 1973 1973-03-02 20:00:00 blood 2691 #> 588 46.0 3 1973 1973-03-02 20:00:00 bone 2691 #> 589 57.7 4 1973 1973-04-02 06:00:00 blood 2692 #> 590 57.7 4 1973 1973-04-02 06:00:00 bone 2692 #> 591 42.4 5 1973 1973-05-02 16:00:00 blood 2693 #> 592 42.4 5 1973 1973-05-02 16:00:00 bone 2693 #> 593 39.5 6 1973 1973-06-02 02:00:00 blood 2694 #> 594 39.5 6 1973 1973-06-02 02:00:00 bone 2694 #> 595 23.1 7 1973 1973-07-02 12:00:00 blood 2695 #> 596 23.1 7 1973 1973-07-02 12:00:00 bone 2695 #> 597 25.6 8 1973 1973-08-01 22:00:00 blood 2696 #> 598 25.6 8 1973 1973-08-01 22:00:00 bone 2696 #> 599 59.3 9 1973 1973-09-01 08:00:00 blood 2697 #> 600 59.3 9 1973 1973-09-01 08:00:00 bone 2697 #> 601 30.7 10 1973 1973-10-01 18:00:00 blood 2698 #> 602 30.7 10 1973 1973-10-01 18:00:00 bone 2698 #> 603 23.9 11 1973 1973-11-01 04:00:00 blood 2699 #> 604 23.9 11 1973 1973-11-01 04:00:00 bone 2699 #> 605 23.3 12 1973 1973-12-01 14:00:00 blood 2700 #> 606 23.3 12 1973 1973-12-01 14:00:00 bone 2700 #> 607 27.6 1 1974 1974-01-01 00:00:00 blood 2701 #> 608 27.6 1 1974 1974-01-01 00:00:00 bone 2701 #> 609 26.0 2 1974 1974-01-31 10:00:00 blood 2702 #> 610 26.0 2 1974 1974-01-31 10:00:00 bone 2702 #> 611 21.3 3 1974 1974-03-02 20:00:00 blood 2703 #> 612 21.3 3 1974 1974-03-02 20:00:00 bone 2703 #> 613 40.3 4 1974 1974-04-02 06:00:00 blood 2704 #> 614 40.3 4 1974 1974-04-02 06:00:00 bone 2704 #> 615 39.5 5 1974 1974-05-02 16:00:00 blood 2705 #> 616 39.5 5 1974 1974-05-02 16:00:00 bone 2705 #> 617 36.0 6 1974 1974-06-02 02:00:00 blood 2706 #> 618 36.0 6 1974 1974-06-02 02:00:00 bone 2706 #> 619 55.8 7 1974 1974-07-02 12:00:00 blood 2707 #> 620 55.8 7 1974 1974-07-02 12:00:00 bone 2707 #> 621 33.6 8 1974 1974-08-01 22:00:00 blood 2708 #> 622 33.6 8 1974 1974-08-01 22:00:00 bone 2708 #> 623 40.2 9 1974 1974-09-01 08:00:00 blood 2709 #> 624 40.2 9 1974 1974-09-01 08:00:00 bone 2709 #> 625 47.1 10 1974 1974-10-01 18:00:00 blood 2710 #> 626 47.1 10 1974 1974-10-01 18:00:00 bone 2710 #> 627 25.0 11 1974 1974-11-01 04:00:00 blood 2711 #> 628 25.0 11 1974 1974-11-01 04:00:00 bone 2711 #> 629 20.5 12 1974 1974-12-01 14:00:00 blood 2712 #> 630 20.5 12 1974 1974-12-01 14:00:00 bone 2712 #> 631 18.9 1 1975 1975-01-01 00:00:00 blood 2713 #> 632 18.9 1 1975 1975-01-01 00:00:00 bone 2713 #> 633 11.5 2 1975 1975-01-31 10:00:00 blood 2714 #> 634 11.5 2 1975 1975-01-31 10:00:00 bone 2714 #> 635 11.5 3 1975 1975-03-02 20:00:00 blood 2715 #> 636 11.5 3 1975 1975-03-02 20:00:00 bone 2715 #> 637 5.1 4 1975 1975-04-02 06:00:00 blood 2716 #> 638 5.1 4 1975 1975-04-02 06:00:00 bone 2716 #> 639 9.0 5 1975 1975-05-02 16:00:00 blood 2717 #> 640 9.0 5 1975 1975-05-02 16:00:00 bone 2717 #> 641 11.4 6 1975 1975-06-02 02:00:00 blood 2718 #> 642 11.4 6 1975 1975-06-02 02:00:00 bone 2718 #> 643 28.2 7 1975 1975-07-02 12:00:00 blood 2719 #> 644 28.2 7 1975 1975-07-02 12:00:00 bone 2719 #> 645 39.7 8 1975 1975-08-01 22:00:00 blood 2720 #> 646 39.7 8 1975 1975-08-01 22:00:00 bone 2720 #> 647 13.9 9 1975 1975-09-01 08:00:00 blood 2721 #> 648 13.9 9 1975 1975-09-01 08:00:00 bone 2721 #> 649 9.1 10 1975 1975-10-01 18:00:00 blood 2722 #> 650 9.1 10 1975 1975-10-01 18:00:00 bone 2722 #> 651 19.4 11 1975 1975-11-01 04:00:00 blood 2723 #> 652 19.4 11 1975 1975-11-01 04:00:00 bone 2723 #> 653 7.8 12 1975 1975-12-01 14:00:00 blood 2724 #> 654 7.8 12 1975 1975-12-01 14:00:00 bone 2724 #> 655 8.1 1 1976 1976-01-01 00:00:00 blood 2725 #> 656 8.1 1 1976 1976-01-01 00:00:00 bone 2725 #> 657 4.3 2 1976 1976-01-31 12:00:00 blood 2726 #> 658 4.3 2 1976 1976-01-31 12:00:00 bone 2726 #> 659 21.9 3 1976 1976-03-02 00:00:00 blood 2727 #> 660 21.9 3 1976 1976-03-02 00:00:00 bone 2727 #> 661 18.8 4 1976 1976-04-01 12:00:00 blood 2728 #> 662 18.8 4 1976 1976-04-01 12:00:00 bone 2728 #> 663 12.4 5 1976 1976-05-02 00:00:00 blood 2729 #> 664 12.4 5 1976 1976-05-02 00:00:00 bone 2729 #> 665 12.2 6 1976 1976-06-01 12:00:00 blood 2730 #> 666 12.2 6 1976 1976-06-01 12:00:00 bone 2730 #> 667 1.9 7 1976 1976-07-02 00:00:00 blood 2731 #> 668 1.9 7 1976 1976-07-02 00:00:00 bone 2731 #> 669 16.4 8 1976 1976-08-01 12:00:00 blood 2732 #> 670 16.4 8 1976 1976-08-01 12:00:00 bone 2732 #> 671 13.5 9 1976 1976-09-01 00:00:00 blood 2733 #> 672 13.5 9 1976 1976-09-01 00:00:00 bone 2733 #> 673 20.6 10 1976 1976-10-01 12:00:00 blood 2734 #> 674 20.6 10 1976 1976-10-01 12:00:00 bone 2734 #> 675 5.2 11 1976 1976-11-01 00:00:00 blood 2735 #> 676 5.2 11 1976 1976-11-01 00:00:00 bone 2735 #> 677 15.3 12 1976 1976-12-01 12:00:00 blood 2736 #> 678 15.3 12 1976 1976-12-01 12:00:00 bone 2736 #> 679 16.4 1 1977 1977-01-01 00:00:00 blood 2737 #> 680 16.4 1 1977 1977-01-01 00:00:00 bone 2737 #> 681 23.1 2 1977 1977-01-31 10:00:00 blood 2738 #> 682 23.1 2 1977 1977-01-31 10:00:00 bone 2738 #> 683 8.7 3 1977 1977-03-02 20:00:00 blood 2739 #> 684 8.7 3 1977 1977-03-02 20:00:00 bone 2739 #> 685 12.9 4 1977 1977-04-02 06:00:00 blood 2740 #> 686 12.9 4 1977 1977-04-02 06:00:00 bone 2740 #> 687 18.6 5 1977 1977-05-02 16:00:00 blood 2741 #> 688 18.6 5 1977 1977-05-02 16:00:00 bone 2741 #> 689 38.5 6 1977 1977-06-02 02:00:00 blood 2742 #> 690 38.5 6 1977 1977-06-02 02:00:00 bone 2742 #> 691 21.4 7 1977 1977-07-02 12:00:00 blood 2743 #> 692 21.4 7 1977 1977-07-02 12:00:00 bone 2743 #> 693 30.1 8 1977 1977-08-01 22:00:00 blood 2744 #> 694 30.1 8 1977 1977-08-01 22:00:00 bone 2744 #> 695 44.0 9 1977 1977-09-01 08:00:00 blood 2745 #> 696 44.0 9 1977 1977-09-01 08:00:00 bone 2745 #> 697 43.8 10 1977 1977-10-01 18:00:00 blood 2746 #> 698 43.8 10 1977 1977-10-01 18:00:00 bone 2746 #> 699 29.1 11 1977 1977-11-01 04:00:00 blood 2747 #> 700 29.1 11 1977 1977-11-01 04:00:00 bone 2747 #> 701 43.2 12 1977 1977-12-01 14:00:00 blood 2748 #> 702 43.2 12 1977 1977-12-01 14:00:00 bone 2748 #> 703 51.9 1 1978 1978-01-01 00:00:00 blood 2749 #> 704 51.9 1 1978 1978-01-01 00:00:00 bone 2749 #> 705 93.6 2 1978 1978-01-31 10:00:00 blood 2750 #> 706 93.6 2 1978 1978-01-31 10:00:00 bone 2750 #> 707 76.5 3 1978 1978-03-02 20:00:00 blood 2751 #> 708 76.5 3 1978 1978-03-02 20:00:00 bone 2751 #> 709 99.7 4 1978 1978-04-02 06:00:00 blood 2752 #> 710 99.7 4 1978 1978-04-02 06:00:00 bone 2752 #> 711 82.7 5 1978 1978-05-02 16:00:00 blood 2753 #> 712 82.7 5 1978 1978-05-02 16:00:00 bone 2753 #> 713 95.1 6 1978 1978-06-02 02:00:00 blood 2754 #> 714 95.1 6 1978 1978-06-02 02:00:00 bone 2754 #> 715 70.4 7 1978 1978-07-02 12:00:00 blood 2755 #> 716 70.4 7 1978 1978-07-02 12:00:00 bone 2755 #> 717 58.1 8 1978 1978-08-01 22:00:00 blood 2756 #> 718 58.1 8 1978 1978-08-01 22:00:00 bone 2756 #> 719 138.2 9 1978 1978-09-01 08:00:00 blood 2757 #> 720 138.2 9 1978 1978-09-01 08:00:00 bone 2757 #> 721 125.1 10 1978 1978-10-01 18:00:00 blood 2758 #> 722 125.1 10 1978 1978-10-01 18:00:00 bone 2758 #> 723 97.9 11 1978 1978-11-01 04:00:00 blood 2759 #> 724 97.9 11 1978 1978-11-01 04:00:00 bone 2759 #> 725 122.7 12 1978 1978-12-01 14:00:00 blood 2760 #> 726 122.7 12 1978 1978-12-01 14:00:00 bone 2760 #> 727 166.6 1 1979 1979-01-01 00:00:00 blood 2761 #> 728 166.6 1 1979 1979-01-01 00:00:00 bone 2761 #> 729 137.5 2 1979 1979-01-31 10:00:00 blood 2762 #> 730 137.5 2 1979 1979-01-31 10:00:00 bone 2762 #> 731 138.0 3 1979 1979-03-02 20:00:00 blood 2763 #> 732 138.0 3 1979 1979-03-02 20:00:00 bone 2763 #> 733 101.5 4 1979 1979-04-02 06:00:00 blood 2764 #> 734 101.5 4 1979 1979-04-02 06:00:00 bone 2764 #> 735 134.4 5 1979 1979-05-02 16:00:00 blood 2765 #> 736 134.4 5 1979 1979-05-02 16:00:00 bone 2765 #> 737 149.5 6 1979 1979-06-02 02:00:00 blood 2766 #> 738 149.5 6 1979 1979-06-02 02:00:00 bone 2766 #> 739 159.4 7 1979 1979-07-02 12:00:00 blood 2767 #> 740 159.4 7 1979 1979-07-02 12:00:00 bone 2767 #> 741 142.2 8 1979 1979-08-01 22:00:00 blood 2768 #> 742 142.2 8 1979 1979-08-01 22:00:00 bone 2768 #> 743 188.4 9 1979 1979-09-01 08:00:00 blood 2769 #> 744 188.4 9 1979 1979-09-01 08:00:00 bone 2769 #> 745 186.2 10 1979 1979-10-01 18:00:00 blood 2770 #> 746 186.2 10 1979 1979-10-01 18:00:00 bone 2770 #> 747 183.3 11 1979 1979-11-01 04:00:00 blood 2771 #> 748 183.3 11 1979 1979-11-01 04:00:00 bone 2771 #> 749 176.3 12 1979 1979-12-01 14:00:00 blood 2772 #> 750 176.3 12 1979 1979-12-01 14:00:00 bone 2772 #> 751 159.6 1 1980 1980-01-01 00:00:00 blood 2773 #> 752 159.6 1 1980 1980-01-01 00:00:00 bone 2773 #> 753 155.0 2 1980 1980-01-31 12:00:00 blood 2774 #> 754 155.0 2 1980 1980-01-31 12:00:00 bone 2774 #> 755 126.2 3 1980 1980-03-02 00:00:00 blood 2775 #> 756 126.2 3 1980 1980-03-02 00:00:00 bone 2775 #> 757 164.1 4 1980 1980-04-01 12:00:00 blood 2776 #> 758 164.1 4 1980 1980-04-01 12:00:00 bone 2776 #> 759 179.9 5 1980 1980-05-02 00:00:00 blood 2777 #> 760 179.9 5 1980 1980-05-02 00:00:00 bone 2777 #> 761 157.3 6 1980 1980-06-01 12:00:00 blood 2778 #> 762 157.3 6 1980 1980-06-01 12:00:00 bone 2778 #> 763 136.3 7 1980 1980-07-02 00:00:00 blood 2779 #> 764 136.3 7 1980 1980-07-02 00:00:00 bone 2779 #> 765 135.4 8 1980 1980-08-01 12:00:00 blood 2780 #> 766 135.4 8 1980 1980-08-01 12:00:00 bone 2780 #> 767 155.0 9 1980 1980-09-01 00:00:00 blood 2781 #> 768 155.0 9 1980 1980-09-01 00:00:00 bone 2781 #> 769 164.7 10 1980 1980-10-01 12:00:00 blood 2782 #> 770 164.7 10 1980 1980-10-01 12:00:00 bone 2782 #> 771 147.9 11 1980 1980-11-01 00:00:00 blood 2783 #> 772 147.9 11 1980 1980-11-01 00:00:00 bone 2783 #> 773 174.4 12 1980 1980-12-01 12:00:00 blood 2784 #> 774 174.4 12 1980 1980-12-01 12:00:00 bone 2784 #> 775 114.0 1 1981 1981-01-01 00:00:00 blood 2785 #> 776 114.0 1 1981 1981-01-01 00:00:00 bone 2785 #> 777 141.3 2 1981 1981-01-31 10:00:00 blood 2786 #> 778 141.3 2 1981 1981-01-31 10:00:00 bone 2786 #> 779 135.5 3 1981 1981-03-02 20:00:00 blood 2787 #> 780 135.5 3 1981 1981-03-02 20:00:00 bone 2787 #> 781 156.4 4 1981 1981-04-02 06:00:00 blood 2788 #> 782 156.4 4 1981 1981-04-02 06:00:00 bone 2788 #> 783 127.5 5 1981 1981-05-02 16:00:00 blood 2789 #> 784 127.5 5 1981 1981-05-02 16:00:00 bone 2789 #> 785 90.0 6 1981 1981-06-02 02:00:00 blood 2790 #> 786 90.0 6 1981 1981-06-02 02:00:00 bone 2790 #> 787 143.8 7 1981 1981-07-02 12:00:00 blood 2791 #> 788 143.8 7 1981 1981-07-02 12:00:00 bone 2791 #> 789 158.7 8 1981 1981-08-01 22:00:00 blood 2792 #> 790 158.7 8 1981 1981-08-01 22:00:00 bone 2792 #> 791 167.3 9 1981 1981-09-01 08:00:00 blood 2793 #> 792 167.3 9 1981 1981-09-01 08:00:00 bone 2793 #> 793 162.4 10 1981 1981-10-01 18:00:00 blood 2794 #> 794 162.4 10 1981 1981-10-01 18:00:00 bone 2794 #> 795 137.5 11 1981 1981-11-01 04:00:00 blood 2795 #> 796 137.5 11 1981 1981-11-01 04:00:00 bone 2795 #> 797 150.1 12 1981 1981-12-01 14:00:00 blood 2796 #> 798 150.1 12 1981 1981-12-01 14:00:00 bone 2796 #> 799 111.2 1 1982 1982-01-01 00:00:00 blood 2797 #> 800 111.2 1 1982 1982-01-01 00:00:00 bone 2797 #> 801 163.6 2 1982 1982-01-31 10:00:00 blood 2798 #> 802 163.6 2 1982 1982-01-31 10:00:00 bone 2798 #> 803 153.8 3 1982 1982-03-02 20:00:00 blood 2799 #> 804 153.8 3 1982 1982-03-02 20:00:00 bone 2799 #> 805 122.0 4 1982 1982-04-02 06:00:00 blood 2800 #> 806 122.0 4 1982 1982-04-02 06:00:00 bone 2800 #> 807 82.2 5 1982 1982-05-02 16:00:00 blood 2801 #> 808 82.2 5 1982 1982-05-02 16:00:00 bone 2801 #> 809 110.4 6 1982 1982-06-02 02:00:00 blood 2802 #> 810 110.4 6 1982 1982-06-02 02:00:00 bone 2802 #> 811 106.1 7 1982 1982-07-02 12:00:00 blood 2803 #> 812 106.1 7 1982 1982-07-02 12:00:00 bone 2803 #> 813 107.6 8 1982 1982-08-01 22:00:00 blood 2804 #> 814 107.6 8 1982 1982-08-01 22:00:00 bone 2804 #> 815 118.8 9 1982 1982-09-01 08:00:00 blood 2805 #> 816 118.8 9 1982 1982-09-01 08:00:00 bone 2805 #> 817 94.7 10 1982 1982-10-01 18:00:00 blood 2806 #> 818 94.7 10 1982 1982-10-01 18:00:00 bone 2806 #> 819 98.1 11 1982 1982-11-01 04:00:00 blood 2807 #> 820 98.1 11 1982 1982-11-01 04:00:00 bone 2807 #> 821 127.0 12 1982 1982-12-01 14:00:00 blood 2808 #> 822 127.0 12 1982 1982-12-01 14:00:00 bone 2808 #> 823 84.3 1 1983 1983-01-01 00:00:00 blood 2809 #> 824 84.3 1 1983 1983-01-01 00:00:00 bone 2809 #> 825 51.0 2 1983 1983-01-31 10:00:00 blood 2810 #> 826 51.0 2 1983 1983-01-31 10:00:00 bone 2810 #> 827 66.5 3 1983 1983-03-02 20:00:00 blood 2811 #> 828 66.5 3 1983 1983-03-02 20:00:00 bone 2811 #> 829 80.7 4 1983 1983-04-02 06:00:00 blood 2812 #> 830 80.7 4 1983 1983-04-02 06:00:00 bone 2812 #> 831 99.2 5 1983 1983-05-02 16:00:00 blood 2813 #> 832 99.2 5 1983 1983-05-02 16:00:00 bone 2813 #> 833 91.1 6 1983 1983-06-02 02:00:00 blood 2814 #> 834 91.1 6 1983 1983-06-02 02:00:00 bone 2814 #> 835 82.2 7 1983 1983-07-02 12:00:00 blood 2815 #> 836 82.2 7 1983 1983-07-02 12:00:00 bone 2815 #> 837 71.8 8 1983 1983-08-01 22:00:00 blood 2816 #> 838 71.8 8 1983 1983-08-01 22:00:00 bone 2816 #> 839 50.3 9 1983 1983-09-01 08:00:00 blood 2817 #> 840 50.3 9 1983 1983-09-01 08:00:00 bone 2817 #> 841 55.8 10 1983 1983-10-01 18:00:00 blood 2818 #> 842 55.8 10 1983 1983-10-01 18:00:00 bone 2818 #> 843 33.3 11 1983 1983-11-01 04:00:00 blood 2819 #> 844 33.3 11 1983 1983-11-01 04:00:00 bone 2819 #> 845 33.4 12 1983 1983-12-01 14:00:00 blood 2820 #> 846 33.4 12 1983 1983-12-01 14:00:00 bone 2820 #> # An xts object example library(xts) #> Loading required package: zoo #> #> Attaching package: 'zoo' #> The following objects are masked from 'package:base': #> #> as.Date, as.Date.numeric dates <- seq(as.Date(\"2001-05-01\"), length=30, by=\"quarter\") data <- cbind(c(gas = rpois(30, cumprod(1+rnorm(30, mean = 0.01, sd = 0.001)))), c(oil = rpois(30, cumprod(1+rnorm(30, mean = 0.01, sd = 0.001))))) series <- xts(x = data, order.by = dates) colnames(series) <- c('gas', 'oil') head(series) #> gas oil #> 2001-05-01 2 2 #> 2001-08-01 0 2 #> 2001-11-01 4 1 #> 2002-02-01 4 2 #> 2002-05-01 2 0 #> 2002-08-01 4 3 series_to_mvgam(series, freq = 4, train_prop = 0.85) #> $data_train #> y season year date series time #> 1 2 2 2001 2001-05-01 gas 1 #> 2 2 2 2001 2001-05-01 oil 1 #> 3 0 3 2001 2001-08-01 gas 2 #> 4 2 3 2001 2001-08-01 oil 2 #> 5 4 4 2001 2001-11-01 gas 3 #> 6 1 4 2001 2001-11-01 oil 3 #> 7 4 1 2002 2002-02-01 gas 4 #> 8 2 1 2002 2002-02-01 oil 4 #> 9 2 2 2002 2002-05-01 gas 5 #> 10 0 2 2002 2002-05-01 oil 5 #> 11 4 3 2002 2002-08-01 gas 6 #> 12 3 3 2002 2002-08-01 oil 6 #> 13 3 4 2002 2002-11-01 gas 7 #> 14 1 4 2002 2002-11-01 oil 7 #> 15 1 1 2003 2003-02-01 gas 8 #> 16 2 1 2003 2003-02-01 oil 8 #> 17 2 2 2003 2003-05-01 gas 9 #> 18 2 2 2003 2003-05-01 oil 9 #> 19 0 3 2003 2003-08-01 gas 10 #> 20 1 3 2003 2003-08-01 oil 10 #> 21 2 4 2003 2003-11-01 gas 11 #> 22 0 4 2003 2003-11-01 oil 11 #> 23 0 1 2004 2004-02-01 gas 12 #> 24 5 1 2004 2004-02-01 oil 12 #> 25 1 2 2004 2004-05-01 gas 13 #> 26 0 2 2004 2004-05-01 oil 13 #> 27 1 3 2004 2004-08-01 gas 14 #> 28 4 3 2004 2004-08-01 oil 14 #> 29 0 4 2004 2004-11-01 gas 15 #> 30 1 4 2004 2004-11-01 oil 15 #> 31 0 1 2005 2005-02-01 gas 16 #> 32 0 1 2005 2005-02-01 oil 16 #> 33 1 2 2005 2005-05-01 gas 17 #> 34 3 2 2005 2005-05-01 oil 17 #> 35 0 3 2005 2005-08-01 gas 18 #> 36 1 3 2005 2005-08-01 oil 18 #> 37 1 4 2005 2005-11-01 gas 19 #> 38 1 4 2005 2005-11-01 oil 19 #> 39 1 1 2006 2006-02-01 gas 20 #> 40 3 1 2006 2006-02-01 oil 20 #> 41 3 2 2006 2006-05-01 gas 21 #> 42 2 2 2006 2006-05-01 oil 21 #> 43 2 3 2006 2006-08-01 gas 22 #> 44 2 3 2006 2006-08-01 oil 22 #> 45 0 4 2006 2006-11-01 gas 23 #> 46 0 4 2006 2006-11-01 oil 23 #> 47 1 1 2007 2007-02-01 gas 24 #> 48 0 1 2007 2007-02-01 oil 24 #> 49 1 2 2007 2007-05-01 gas 25 #> 50 0 2 2007 2007-05-01 oil 25 #> #> $data_test #> y season year date series time #> 1 0 3 2007 2007-08-01 gas 26 #> 2 0 3 2007 2007-08-01 oil 26 #> 3 2 4 2007 2007-11-01 gas 27 #> 4 0 4 2007 2007-11-01 oil 27 #> 5 4 1 2008 2008-02-01 gas 28 #> 6 0 1 2008 2008-02-01 oil 28 #> 7 3 2 2008 2008-05-01 gas 29 #> 8 3 2 2008 2008-05-01 oil 29 #> 9 2 3 2008 2008-08-01 gas 30 #> 10 1 3 2008 2008-08-01 oil 30 #>"},{"path":"https://nicholasjclark.github.io/mvgam/reference/sim_mvgam.html","id":null,"dir":"Reference","previous_headings":"","what":"Simulate a set of discrete time series for mvgam modelling — sim_mvgam","title":"Simulate a set of discrete time series for mvgam modelling — sim_mvgam","text":"function simulates discrete time series data fitting multivariate GAM includes shared seasonality dependence state-space latent dynamic factors. Random dependencies among series, .e. correlations long-term trends, included form correlated loadings latent dynamic factors","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/sim_mvgam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Simulate a set of discrete time series for mvgam modelling — sim_mvgam","text":"","code":"sim_mvgam( T = 100, n_series = 3, seasonality = \"shared\", use_lv = FALSE, n_lv = 1, trend_model = \"RW\", drift = FALSE, trend_rel = 0.2, freq = 12, family = poisson(), phi, shape, sigma, nu, mu, prop_missing = 0, prop_train = 0.85 )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/sim_mvgam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Simulate a set of discrete time series for mvgam modelling — sim_mvgam","text":"T integer. Number observations (timepoints) n_series integer. Number discrete time series seasonality character. Either shared, meaning series share exact seasonal pattern, hierarchical, meaning global seasonality series' pattern can deviate slightly use_lv logical. TRUE, use dynamic factors estimate series' latent trends reduced dimension format. FALSE, estimate independent latent trends series n_lv integer. Number latent dynamic factors generating series' trends trend_model character specifying time series dynamics latent trend. Options : None (latent trend component; .e. GAM component contributes linear predictor, observation process source error; similarly estimated gam) RW (random walk possible drift) AR1 (possible drift) AR2 (possible drift) AR3 (possible drift) VAR1 (contemporaneously uncorrelated VAR1) VAR1cor (contemporaneously correlated VAR1) GP (Gaussian Process squared exponential kernel) See mvgam_trends details drift logical, simulate drift term trend trend_rel numeric. Relative importance trend series. 0 1 freq integer. seasonal frequency series family family specifying exponential observation family series. Currently supported families : nb(), poisson(), tweedie(), gaussian(), betar(), lognormal(), student_t() Gamma() phi vector dispersion parameters series (.e. size Negative Binomial phi Tweedie Beta). length(phi) < n_series, first element phi replicated n_series times. Defaults 5 Negative Binomial Tweedie; 10 Beta shape vector shape parameters series (.e. shape Gamma) length(shape) < n_series, first element shape replicated n_series times. Defaults 10 sigma vector scale parameters series (.e. sd Normal Student-T, log(sd) LogNormal). length(sigma) < n_series, first element sigma replicated n_series times. Defaults 0.5 Normal Student-T; 0.2 Lognormal nu vector degrees freedom parameters series (.e. nu Student-T) length(nu) < n_series, first element nu replicated n_series times. Defaults 3 mu vector location parameters series. length(mu) < n_series, first element mu replicated n_series times. Defaults small random values -0.5 0.5 link scale prop_missing numeric stating proportion observations missing. 0 0.8, inclusive prop_train numeric stating proportion data use training. 0.25 0.75","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/sim_mvgam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Simulate a set of discrete time series for mvgam modelling — sim_mvgam","text":"list object containing outputs needed mvgam, including 'data_train' 'data_test', well additional information simulated seasonality trend dependencies","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/sim_mvgam.html","id":"ref-examples","dir":"Reference","previous_headings":"","what":"Examples","title":"Simulate a set of discrete time series for mvgam modelling — sim_mvgam","text":"","code":"#Simulate series with observations bounded at 0 and 1 (Beta responses) sim_data <- sim_mvgam(family = betar(), trend_model = 'GP', trend_rel = 0.6) plot_mvgam_series(data = sim_data$data_train, series = 'all') #Now simulate series with overdispersed discrete observations sim_data <- sim_mvgam(family = nb(), trend_model = 'GP', trend_rel = 0.6, phi = 10) plot_mvgam_series(data = sim_data$data_train, series = 'all')"},{"path":"https://nicholasjclark.github.io/mvgam/reference/summary.mvgam.html","id":null,"dir":"Reference","previous_headings":"","what":"Summary for a fitted mvgam object — summary.mvgam","title":"Summary for a fitted mvgam object — summary.mvgam","text":"functions take fitted mvgam object return various useful summaries","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/summary.mvgam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Summary for a fitted mvgam object — summary.mvgam","text":"","code":"# S3 method for mvgam summary(object, ...) # S3 method for mvgam_prefit summary(object, ...) # S3 method for mvgam coef(object, summarise = TRUE, ...)"},{"path":"https://nicholasjclark.github.io/mvgam/reference/summary.mvgam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Summary for a fitted mvgam object — summary.mvgam","text":"object list object returned mvgam ... Ignored summarise logical. Summaries coefficients returned TRUE. Otherwise full posterior distribution returned","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/summary.mvgam.html","id":"value","dir":"Reference","previous_headings":"","what":"Value","title":"Summary for a fitted mvgam object — summary.mvgam","text":"summary.mvgam summary.mvgam_prefit, Aalist printed -screen showing summaries model coef.mvgam, either matrix posterior coefficient distributions (summarise == FALSE data.frame coefficient summaries)","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/summary.mvgam.html","id":"details","dir":"Reference","previous_headings":"","what":"Details","title":"Summary for a fitted mvgam object — summary.mvgam","text":"summary.mvgam summary.mvgam_prefit return brief summaries model's call printed, along posterior intervals key parameters model. Note smooths extra penalties null space, summaries rho parameters may include penalty terms number smooths original model formula. coef.mvgam returns either summaries full posterior estimates GAM component coefficients","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/summary.mvgam.html","id":"author","dir":"Reference","previous_headings":"","what":"Author","title":"Summary for a fitted mvgam object — summary.mvgam","text":"Nicholas J Clark","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/update.mvgam.html","id":null,"dir":"Reference","previous_headings":"","what":"Update an existing mvgam object — update.mvgam","title":"Update an existing mvgam object — update.mvgam","text":"function allows previously fitted mvgam model updated","code":""},{"path":"https://nicholasjclark.github.io/mvgam/reference/update.mvgam.html","id":"ref-usage","dir":"Reference","previous_headings":"","what":"Usage","title":"Update an existing mvgam object — update.mvgam","text":"","code":"# S3 method for mvgam update( object, formula, trend_formula, data, newdata, trend_model, trend_map, use_lv, n_lv, family, priors, ... )"},{"path":"https://nicholasjclark.github.io/mvgam/reference/update.mvgam.html","id":"arguments","dir":"Reference","previous_headings":"","what":"Arguments","title":"Update an existing mvgam object — update.mvgam","text":"object fitted mvgam model formula Optional new formula object. Note, mvgam currently support dynamic formula updates removal specific terms - term. updating, entire formula needs supplied trend_formula optional character string specifying GAM process model formula. supplied, linear predictor modelled latent trends capture process model evolution separately observation model. response variable specified left-hand side formula (.e. valid option ~ season + s(year)). feature experimental, currently available Random Walk trend models. data dataframe list containing model response variable covariates required GAM formula. include columns: 'series' (character factor index series IDs) 'time' (numeric index time point observation). variables included linear predictor formula must also present newdata Optional dataframe list test data containing least 'series' 'time' addition variables included linear predictor formula. included, observations variable y set NA fitting model posterior simulations can obtained trend_model character specifying time series dynamics latent trend. Options : None (latent trend component; .e. GAM component contributes linear predictor, observation process source error; similarly estimated gam) RW (random walk possible drift) AR1 (possible drift) AR2 (possible drift) AR3 (possible drift) VAR1 (possible drift; available Stan) GP (Gaussian Process squared exponential kernel; available Stan) trend_map Optional data.frame specifying series depend latent trends. Useful allowing multiple series depend latent trend process, different observation processes. supplied, latent factor model set setting use_lv = TRUE using mapping set shared trends. Needs column names series trend, integer values trend column state trend series depend . series column single unique entry series data (names perfectly match factor levels series variable data). See examples mvgam details use_lv logical. TRUE, use dynamic factors estimate series' latent trends reduced dimension format. FALSE, estimate independent latent trends series n_lv integer number latent dynamic factors use use_lv == TRUE. >n_series. Defaults arbitrarily min(2, floor(n_series / 2)) family family specifying exponential observation family series. Currently supported families : nb(), poisson(), tweedie(), gaussian(), betar(), lognormal(), student_t() Gamma() priors optional data.frame prior definitions. See get_mvgam_priors mvgam information changing default prior distributions ... arguments passed mvgam","code":""}] diff --git a/docs/sitemap.xml b/docs/sitemap.xml index b6d2c725..65802532 100644 --- a/docs/sitemap.xml +++ b/docs/sitemap.xml @@ -33,6 +33,9 @@ https://nicholasjclark.github.io/mvgam/reference/forecast.mvgam.html + + https://nicholasjclark.github.io/mvgam/reference/formula.mvgam.html + https://nicholasjclark.github.io/mvgam/reference/get_monitor_pars.html @@ -57,6 +60,9 @@ https://nicholasjclark.github.io/mvgam/reference/lv_correlations.html + + https://nicholasjclark.github.io/mvgam/reference/model.frame.mvgam.html + https://nicholasjclark.github.io/mvgam/reference/mvgam-class.html @@ -72,6 +78,9 @@ https://nicholasjclark.github.io/mvgam/reference/mvgam_forecast-class.html + + https://nicholasjclark.github.io/mvgam/reference/mvgam_marginaleffects.html + https://nicholasjclark.github.io/mvgam/reference/mvgam_trends.html