Merge pull request #93 from spsanderson/development

Fix #91

NEWS.md

@@ -1,5 +1,10 @@
 # TidyDensity (development version)
 
+## Breaking Changes
+1. Fix #91 - Bug fix, change `tidy_gamma()` parameter of `.rate` to `.scale
+Fix `tidy_autoplot_` functions to incorprate this change. Fix `util_gamma_param_estimate()`
+to say `scale` instead of `rate` in the returned estimated parameters.
+
 # TidyDensity 1.0.0
 
 ## Breaking Changes

R/autoplot-density.R

@@ -118,7 +118,7 @@ tidy_autoplot <- function(.data, .plot_type = "density", .line_size = .5,
     "Parameters: ", if (atb$tibble_type == "tidy_gaussian") {
       paste0("Mean: ", atb$.mean, " - SD: ", atb$.sd)
     } else if (atb$tibble_type == "tidy_gamma") {
-      paste0("Shape: ", atb$.shape, " - Rate: ", atb$.rate)
+      paste0("Shape: ", atb$.shape, " - Scale: ", atb$.scale)
     } else if (atb$tibble_type == "tidy_beta") {
       paste0("Shape1: ", atb$.shape1, " - Shape2: ", atb$.shape2, " - NCP: ", atb$.ncp)
     } else if (atb$tibble_type %in% c("tidy_poisson", "tidy_zero_truncated_poisson")) {

R/autoplot-multi-dist.R

@@ -124,7 +124,7 @@ tidy_multi_dist_autoplot <- function(.data, .plot_type = "density", .line_size =
         "Parameters: ", if (atb$all$tibble_type == "tidy_gaussian") {
             paste0("Mean: ", toString(atb$.param_list$.mean), " - SD: ", toString(atb$.param_list$.sd))
         } else if (atb$all$tibble_type == "tidy_gamma") {
-            paste0("Shape: ", toString(atb$.param_list$.shape), " - Rate: ", toString(atb$.param_list$.rate))
+            paste0("Shape: ", toString(atb$.param_list$.shape), " - Scale: ", toString(atb$.param_list$.scale))
         } else if (atb$all$tibble_type == "tidy_beta") {
             paste0("Shape1: ", toString(atb$.param_list$.shape1), " - Shape2: ", toString(atb$.param_list$.shape2), " - NCP: ", toString(atb$.param_list$.ncp))
         } else if (atb$all$tibble_type %in% c("tidy_poisson", "tidy_zero_truncated_poisson")) {

R/est-param-gamma.R

@@ -7,7 +7,7 @@
 #'
 #' @details This function will see if the given vector `.x` is a numeric vector.
 #'
-#' @description This function will attempt to estimate the gamma shape and rate
+#' @description This function will attempt to estimate the gamma shape and scale
 #' parameters given some vector of values. The function will return a list output by default, and  if the parameter
 #' `.auto_gen_empirical` is set to `TRUE` then the empirical data given to the
 #' parameter `.x` will be run through the `tidy_empirical()` function and combined
@@ -23,7 +23,7 @@
 #' library(dplyr)
 #' library(ggplot2)
 #'
-#' tg <- tidy_gamma(.shape = 1, .rate = .5) %>% pull(y)
+#' tg <- tidy_gamma(.shape = 1, .scale = .3) %>% pull(y)
 #' output <- util_gamma_param_estimate(tg)
 #'
 #' output$parameter_tbl
@@ -76,19 +76,19 @@ util_gamma_param_estimate <- function(.x, .auto_gen_empirical = TRUE){
     # Parameters ----
     # NIST
     nist_shape <- (m/s)^2
-    nist_rate <- (s^2)/m
+    nist_scale <- (s^2)/m
 
     # EnvStats
     es_mmu_shape <- (m/(sqrt(n/(n - 1)) * s))^2
-    es_mmu_rate <- m/nist_shape
+    es_mmu_scale <- m/nist_shape
 
     es_bcmle_shape <- ((n - 3)/n) * nist_shape + (2/(3 * n))
-    es_bcmle_rate <- m/nist_shape
+    es_bcmle_scale <- m/nist_shape
 
     # Return Tibble ----
     if (.auto_gen_empirical){
         te <- tidy_empirical(.x = x_term)
-        td <- tidy_gamma(.n = n, .shape = round(nist_shape, 3), .rate = round(nist_rate, 3))
+        td <- tidy_gamma(.n = n, .shape = round(nist_shape, 3), .scale = round(nist_scale, 3))
         combined_tbl <- tidy_combine_distributions(te, td)
     }
 
@@ -101,9 +101,9 @@ util_gamma_param_estimate <- function(.x, .auto_gen_empirical = TRUE){
         variance = rep(s, 3),
         method = c("NIST_MME", "EnvStats_MMUE", "EnvStats_BCMLE"),
         shape = c(nist_shape, es_mmu_shape, es_bcmle_shape),
-        rate = c(nist_rate, es_mmu_rate, es_bcmle_rate),
-        shape_ratio = c(nist_shape/nist_rate, es_mmu_shape/es_mmu_rate,
-                        es_bcmle_shape/es_bcmle_rate)
+        scale = c(nist_scale, es_mmu_scale, es_bcmle_scale),
+        shape_ratio = c(nist_shape/nist_scale, es_mmu_shape/es_mmu_scale,
+                        es_bcmle_shape/es_bcmle_scale)
     )
 
     # Return ----

R/random-tidy-gamma.R

@@ -43,87 +43,86 @@
 #' @export
 #'
 
-tidy_gamma <- function(.n = 50, .shape = 1, .rate = 1, .num_sims = 1) {
+tidy_gamma <- function(.n = 50, .shape = 1, .scale = 0.3, .num_sims = 1) {
 
-  # Tidyeval ----
-  n <- as.integer(.n)
-  num_sims <- as.integer(.num_sims)
-  shp <- .shape
-  rte <- .rate
+    # Tidyeval ----
+    n <- as.integer(.n)
+    num_sims <- as.integer(.num_sims)
+    shp <- .shape
+    scle <- .scale
 
-  # Checks ----
-  if (!is.integer(n) | n < 0) {
-    rlang::abort(
-      "The parameters '.n' must be of class integer. Please pass a whole
+    # Checks ----
+    if (!is.integer(n) | n < 0) {
+        rlang::abort(
+            "The parameters '.n' must be of class integer. Please pass a whole
             number like 50 or 100. It must be greater than 0."
-    )
-  }
+        )
+    }
 
-  if (!is.integer(num_sims) | num_sims < 0) {
-    rlang::abort(
-      "The parameter `.num_sims' must be of class integer. Please pass a
+    if (!is.integer(num_sims) | num_sims < 0) {
+        rlang::abort(
+            "The parameter `.num_sims' must be of class integer. Please pass a
             whole number like 50 or 100. It must be greater than 0."
-    )
-  }
+        )
+    }
 
-  if (!is.numeric(shp) | shp < 0) {
-    rlang::abort(
-      "The parameters of '.shape' and '.rate' must be of class numeric.
+    if (!is.numeric(shp) | shp < 0) {
+        rlang::abort(
+            "The parameters of '.shape' and '.scale' must be of class numeric.
             Please pass a numer like 1 or 1.1 etc. and must be greater than 0."
-    )
-  }
+        )
+    }
 
-  if (!is.numeric(rte) | rte < 0) {
-    rlang::abort(
-      "The parameters of '.shape' and '.rate' must be of class numeric.
+    if (!is.numeric(scle) | scle < 0) {
+        rlang::abort(
+            "The parameters of '.shape' and '.scale' must be of class numeric.
             Please pass a numer like 1 or 1.1 etc."
-    )
-  }
+        )
+    }
 
-  x <- seq(1, num_sims, 1)
+    x <- seq(1, num_sims, 1)
 
-  # ps <- seq(-n, n - 1, 2)
-  qs <- seq(0, 1, (1 / (n - 1)))
-  ps <- qs
+    qs <- seq(0, 1, (1 / (n - 1)))
+    ps <- qs
 
-  df <- dplyr::tibble(sim_number = as.factor(x)) %>%
-    dplyr::group_by(sim_number) %>%
-    dplyr::mutate(x = list(1:n)) %>%
-    dplyr::mutate(y = list(stats::rgamma(n = n, shape = shp, rate = rte))) %>%
-    dplyr::mutate(d = list(density(unlist(y), n = n)[c("x", "y")] %>%
-      purrr::set_names("dx", "dy") %>%
-      dplyr::as_tibble())) %>%
-    dplyr::mutate(p = list(stats::pgamma(ps, shape = shp, rate = rte))) %>%
-    dplyr::mutate(q = list(stats::qgamma(qs, shape = shp, rate = rte))) %>%
-    tidyr::unnest(cols = c(x, y, d, p, q)) %>%
-    dplyr::ungroup()
+    df <- dplyr::tibble(sim_number = as.factor(x)) %>%
+        dplyr::group_by(sim_number) %>%
+        dplyr::mutate(x = list(1:n)) %>%
+        dplyr::mutate(y = list(stats::rgamma(n = n, shape = shp, scale = scle))) %>%
+        dplyr::mutate(d = list(density(unlist(y), n = n)[c("x", "y")] %>%
+                                   purrr::set_names("dx", "dy") %>%
+                                   dplyr::as_tibble())) %>%
+        dplyr::mutate(p = list(stats::pgamma(ps, shape = shp, scale = scle))) %>%
+        dplyr::mutate(q = list(stats::qgamma(qs, shape = shp, scale = scle))) %>%
+        tidyr::unnest(cols = c(x, y, d, p, q)) %>%
+        dplyr::ungroup()
 
-  param_grid <- dplyr::tibble(.shape, .rate)
+    param_grid <- dplyr::tibble(.shape, .scale)
 
-  # Attach descriptive attributes to tibble
-  attr(df, ".shape") <- .shape
-  attr(df, ".rate") <- .rate
-  attr(df, ".n") <- .n
-  attr(df, ".num_sims") <- .num_sims
-  attr(df, "tibble_type") <- "tidy_gamma"
-  attr(df, "ps") <- ps
-  attr(df, "qs") <- qs
-  attr(df, "param_grid") <- param_grid
-  attr(df, "param_grid_txt") <- paste0(
-    "c(",
-    paste(param_grid[, names(param_grid)], collapse = ", "),
-    ")"
-  )
-  attr(df, "dist_with_params") <- paste0(
-    "Gamma",
-    " ",
-    paste0(
-      "c(",
-      paste(param_grid[, names(param_grid)], collapse = ", "),
-      ")"
+    # Attach descriptive attributes to tibble
+    attr(df, ".shape") <- .shape
+    attr(df, ".scale") <- .scale
+    attr(df, ".n") <- .n
+    attr(df, ".num_sims") <- .num_sims
+    attr(df, "tibble_type") <- "tidy_gamma"
+    attr(df, "ps") <- ps
+    attr(df, "qs") <- qs
+    attr(df, "param_grid") <- param_grid
+    attr(df, "param_grid_txt") <- paste0(
+        "c(",
+        paste(param_grid[, names(param_grid)], collapse = ", "),
+        ")"
+    )
+    attr(df, "dist_with_params") <- paste0(
+        "Gamma",
+        " ",
+        paste0(
+            "c(",
+            paste(param_grid[, names(param_grid)], collapse = ", "),
+            ")"
+        )
     )
-  )
 
-  # Return final result as function output
-  return(df)
+    # Return final result as function output
+    return(df)
 }

docs/pkgdown.yml

@@ -3,7 +3,7 @@ pkgdown: 2.0.2
 pkgdown_sha: ~
 articles:
   getting-started: getting-started.html
-last_built: 2022-03-08T21:44Z
+last_built: 2022-03-16T18:55Z
 urls:
   reference: https://github.com/spsanderson/TidyDensity/reference
   article: https://github.com/spsanderson/TidyDensity/articles