Merge pull request #32 from spsanderson/development

Development

R/auto-rw30.R

@@ -80,7 +80,7 @@ rw30 <- function() {
   attr(walks_long, "mu") <- mu
   attr(walks_long, "sd") <- sd
   attr(walks_long, "fns") <- "rw30"
-  attr(res, "dimension")     <- 1
+  attr(walks_long, "dimension")     <- 1
 
   return(walks_long)
 }

R/gen-brown-motion.R

@@ -52,7 +52,7 @@ NULL
 #' @export
 #' @rdname brownian_motion
 
-brownian_motion <- function(.n = 100, .num_walks = 10, .delta_time = 1,
+brownian_motion <- function(.num_walks = 10, .n = 100, .delta_time = 1,
                                .initial_value = 0, .return_tibble = TRUE) {
 
   # Tidyeval ----
@@ -84,11 +84,11 @@ brownian_motion <- function(.n = 100, .num_walks = 10, .delta_time = 1,
   colnames(rand_matrix) <- 1:num_sims
 
   # Get the Brownian Motion and convert to price paths
-  ret <- apply(rbind(rep(initial_value, num_sims), rand_matrix), 2, cumsum)
+  res <- apply(rbind(rep(initial_value, num_sims), rand_matrix), 2, cumsum)
 
   # Return
   if (return_tibble){
-    ret <- ret |>
+    res <- res |>
       dplyr::as_tibble() |>
       dplyr::mutate(t = 1:(t+1)) |>
       tidyr::pivot_longer(-t) |>
@@ -99,13 +99,13 @@ brownian_motion <- function(.n = 100, .num_walks = 10, .delta_time = 1,
   }
 
   # Return ----
-  attr(ret, "time") <- .n
-  attr(ret, "num_sims") <- .num_walks
-  attr(ret, "delta_time") <- .delta_time
-  attr(ret, "initial_value") <- .initial_value
-  attr(ret, "return_tibble") <- .return_tibble
-  attr(ret, "fns") <- "brownian_motion"
+  attr(res, "n") <- .n
+  attr(res, "num_walks") <- .num_walks
+  attr(res, "delta_time") <- .delta_time
+  attr(res, "initial_value") <- .initial_value
+  attr(res, "return_tibble") <- .return_tibble
+  attr(res, "fns") <- "brownian_motion"
   attr(res, "dimension")     <- 1
 
-  return(ret)
+  return(res)
 }

R/gen-discrete-walk.R

@@ -78,8 +78,8 @@ discrete_walk <- function(.num_walks = 25, .n = 100, .upper_bound = 1,
     dplyr::ungroup()
 
   # Attributes
-  attr(res, "num_walks")     <- num_walks
-  attr(res, "n")             <- n
+  attr(res, "n")             <- periods
+  attr(res, "num_walks")     <- .num_walks
   attr(res, "upper_bound")   <- upper_bound
   attr(res, "lower_bound")   <- lower_bound
   attr(res, "upper_probability") <- upper_probability

R/gen-geom-brown-motion.R

@@ -101,12 +101,12 @@ geometric_brownian_motion <- function(.num_walks = 25, .n = 100,
   colnames(rand_matrix) <- 1:num_sims
 
   # get GBM and convert to price paths
-  ret <- exp((mu - sigma * sigma / 2) * delta_time + sigma * rand_matrix * sqrt(delta_time))
-  ret <- apply(rbind(rep(initial_value, num_sims), ret), 2, cumprod)
+  res <- exp((mu - sigma * sigma / 2) * delta_time + sigma * rand_matrix * sqrt(delta_time))
+  res <- apply(rbind(rep(initial_value, num_sims), res), 2, cumprod)
 
   # Return
   if (return_tibble){
-    ret <- ret |>
+    res <- res |>
       dplyr::as_tibble() |>
       dplyr::mutate(t = 1:(t+1)) |>
       tidyr::pivot_longer(-t) |>
@@ -116,15 +116,15 @@ geometric_brownian_motion <- function(.num_walks = 25, .n = 100,
       dplyr::arrange(walk_number, x)
   }
 
-  attr(ret, "time") <- .n
-  attr(ret, "num_sims") <- .num_walks
-  attr(ret, "mean") <- .mu
-  attr(ret, "sigma") <- .sigma
-  attr(ret, "initial_value") <- .initial_value
-  attr(ret, "delta_time") <- .delta_time
-  attr(ret, "return_tibble") <- .return_tibble
-  attr(ret, "fns") <- "geometric_brownian_motion"
+  attr(res, "n") <- .n
+  attr(res, "num_walks") <- .num_walks
+  attr(res, "mean") <- .mu
+  attr(res, "sigma") <- .sigma
+  attr(res, "initial_value") <- .initial_value
+  attr(res, "delta_time") <- .delta_time
+  attr(res, "return_tibble") <- .return_tibble
+  attr(res, "fns") <- "geometric_brownian_motion"
   attr(res, "dimension")     <- 1
 
-  return(ret)
+  return(res)
 }

R/gen-random-drift-walk.R

@@ -84,13 +84,13 @@ random_normal_drift_walk <- function(.num_walks = 25, .n = 100, .mu = 0,
     dplyr::select(walk_number, x, y) |>
     dplyr::arrange(walk_number, x)
 
+  attr(walks_long, "n") <- num_steps
   attr(walks_long, "num_walks") <- num_walks
-  attr(walks_long, "num_steps") <- num_steps
   attr(walks_long, "mu") <- mu
   attr(walks_long, "sd") <- sd
   attr(walks_long, "drift") <- drift
   attr(walks_long, "fns") <- "random_normal_drift_walk"
-  attr(res, "dimension")     <- 1
+  attr(walks_long, "dimension")     <- 1
 
   return(walks_long)
 }

R/gen-random-normal-walk.R

@@ -133,8 +133,8 @@ random_normal_walk <- function(.num_walks = 25, .n = 100, .mu = 0, .sd = .1,
   #   dplyr::ungroup()
 
   # Attributes
-  attr(res, "num_walks")     <- num_walks
   attr(res, "n")             <- n
+  attr(res, "num_walks")     <- num_walks
   attr(res, "mu")            <- mu
   attr(res, "sd")            <- sd
   attr(res, "initial_value") <- initial_value

docs/pkgdown.yml

@@ -3,7 +3,7 @@ pkgdown: 2.1.0
 pkgdown_sha: ~
 articles:
   getting-started: getting-started.html
-last_built: 2024-07-19T16:59Z
+last_built: 2024-07-20T00:41Z
 urls:
   reference: https://www.spsanderson.com/RandomWalker/reference
   article: https://www.spsanderson.com/RandomWalker/articles