BayesTools 0.2.18

Features

• adding prior_mixture() function for creating a mixture of prior distributions
• adding as_mixed_posteriors() and as_marginal_inference() functions for a single JAGS models (with spike and slab or mixture priors) to enabling tables and figures based on the corresponding output
• adding interpret2() function for another way of creating textual summaries without the need of inference and samples objects
• speedup and improvements to the runjags_estimates_table() function

Fixes

• small fixes for expansion of the RoBMA functionality

BayesTools 0.2.17

Features

• adding informed prior distributions for dichotomous and time-to-event outcomes based on Cochrane Database of Systematic Reviews to prior_informed() function
• adding bridge object convenience function bridge_object() (fixes: #28)
• adding Na/NaN tests for check_ functions (fixes: #26)

Fixes

• ability to run more than 4 chains (fixes: #20)

BayesTools 0.2.16

Features

• update an existing JAGS fit with JAGS_extend() function
• new element of the autofit_control argument in JAGS_fit(): "restarts" allows to restart model initialization up to restarts times in case of failure

BayesTools 0.2.15

Fixes

• fixing repeated print of previous prior distribution in model_summary_table() in case of prior_none()

BayesTools 0.2.14

Features

• adding contrast = "meandif" to the prior_factor function which generates identical prior distributions for difference between the grand mean and each factor level
• adding contrast = "independent" to the prior_factor function which generates independent identical prior distributions for each factor level
• remove_column function for removing columns from BayesTools_table objects without breaking the attributes etc...
• adding empty table functions (#10)
• adding remove_parameters argument to model_summary_table()
• adding multivariate point distribution functions
• adding point prior distribution as option to prior_factor with "meandif" and "orthonormal" contrasts
• adding marginal_posterior() function which creates marginal prior and posterior distributions (according to a model formula specification)
• adding Savage_Dickey_BF() function to compute density ratio Bayes factors based on marginal_posterior objects
• adding marginal_inference() function to combine information from marginal_posterior() and Savage_Dickey_BF()
• adding marginal_estimates_table() function to summarize marginal_inference() objects
• adding plot_marginal() function to visualize marginal_inference() objects

Changes

• contrast = "meandif" is now the default setting for prior_factor function
• depreciating transform_orthonormal argument in favor of more general transform_factors argument
• switching dummy contrast/factor attributes to treatment for consistency (#23)

Fixes

• zero length inputs to check_bool(), check_char(), check_real(), check_int(), and check_list() do not throw error if allow_NULL = TRUE
• properly aggregating identical priors in the plotting function (previously overlying multiple spikes on top of each other when attributes did not match)
• student-t allowed as a prior distribution name
• fixing factor contrast settings in JAGS_evaluate_formula
• fixing spike prior transformations

BayesTools 0.2.13

Features

• runjags_estimates_table() function can now handle factor transformations
• plot_posterior function can now handle factor transformations
• ability to remove parameters from the runjags_estimates_table() function via the remove_parameters argument

Fixes

• inability to deal with constant intercept in marglik formula calculation
• runjags_estimates_table() function can now remove factor spike prior distributions
• marginal likelihood calculation for factor prior distributions with spike
• mixing samples from vector priors of length 1
• same prior distributions not always combined together properly when part of them was generated via the formula interface

BayesTools 0.2.12

Features

• stan_estimates_summary() function
• reducing dependency on runjags/rjags

Fixes

• dealing with posterior samples from rstan
• dealing with vector posterior samples
• fixing MCMC error of SD calculation for transformed samples (previously reported 100 times lower)

BayesTools 0.2.11

Features

• adding Bernoulli prior distribution
• adding spike and slab type of prior distributions (without marginal likelihood computations/model-averaging capabilities)
• new vignette comparing Bayes factor computation via marginal likelihood and spike and slab priors

Fixes

• when a transformation is applied, JAGS summary tables now produce the mean of the transformed variable (previous versions incorrectly returned transformation of the mean)

Changes

• runjags_XXX_table functions are now also exported as JAGS_XXX_functions for consistency with the rest of the code

BayesTools 0.2.10

Features

• trace, density, and autocorrelation diagnostic plots for JAGS models

BayesTools 0.2.9

Fixes

• dealing with NaNs in inclusion Bayes factors due to overflow with very large marginal likelihoods