Fix #38

NAMESPACE

@@ -20,6 +20,7 @@ export(tidy_gamma)
 export(tidy_generalized_pareto)
 export(tidy_geometric)
 export(tidy_hypergeometric)
+export(tidy_inverse_exponential)
 export(tidy_inverse_pareto)
 export(tidy_logistic)
 export(tidy_lognormal)

NEWS.md

@@ -18,6 +18,7 @@ None
 12. Fix #60 - Add function `tidy_random_walk_autoplot()`
 13. Fix #47 - Add function `tidy_generalized_pareto()`
 14. Fix #44 - Add function `tidy_paralogistic()`
+15. Fix #38 - Add function `tidy_inverse_exponential()`
 
 ## Fixes and Minor Improvements
 1. Fix #30 - Move `crayon`, `rstudioapi`, and `cli` from Suggests to Imports due to `pillar`

R/autoplot-density.R

@@ -87,7 +87,7 @@ tidy_autoplot <- function(.data, .plot_type = "density", .line_size = .5,
     "tidy_zero_truncated_poisson", "tidy_zero_truncated_geometric",
     "tidy_zero_truncated_binomial", "tidy_zero_truncated_negative_binomial",
     "tidy_pareto_single_parameter", "tidy_pareto", "tidy_inverse_pareto",
-    "tidy_generalized_pareto","tidy_paralogistic"
+    "tidy_generalized_pareto","tidy_paralogistic", "tidy_inverse_exponential"
   )) {
     rlang::abort("The data passed must come from a `tidy_` distribution function.")
   }
@@ -164,6 +164,8 @@ tidy_autoplot <- function(.data, .plot_type = "density", .line_size = .5,
       paste0("Shape: ", atb$.shape, " - ",
              "Rate: ", atb$.rate, " - ",
              "Scale: ", atb$.scale)
+    } else if (atb$tibble_type == "tidy_inverse_exponential"){
+      paste0("Rate: ", atb$.rate, " - Scale: ", atb$.scale)
     }
   )
 

R/random-tidy-exponential-inverse.R

@@ -0,0 +1,109 @@
+#' Tidy Randomly Generated Inverse Exponential Distribution Tibble
+#'
+#' @family Continuous Distribution
+#' @family Exponential
+#'
+#' @author Steven P. Sanderson II, MPH
+#'
+#' @seealso \url{https://openacttexts.github.io/Loss-Data-Analytics/C-SummaryDistributions.html}
+#'
+#' @details This function uses the underlying `actuar::rinvexp()`, and its underlying
+#' `p`, `d`, and `q` functions. For more information please see [actuar::rinvexp()]
+#'
+#' @description This function will generate `n` random points from an inverse exponential
+#' distribution with a user provided, `.rate` or `.scale` and number of
+#' random simulations to be produced. The function returns a tibble with the
+#' simulation number column the x column which corresponds to the n randomly
+#' generated points, the `d_`, `p_` and `q_` data points as well.
+#'
+#' The data is returned un-grouped.
+#'
+#' The columns that are output are:
+#'
+#' -  `sim_number` The current simulation number.
+#' -  `x` The current value of `n` for the current simulation.
+#' -  `y` The randomly generated data point.
+#' -  `dx` The `x` value from the [stats::density()] function.
+#' -  `dy` The `y` value from the [stats::density()] function.
+#' -  `p` The values from the resulting p_ function of the distribution family.
+#' -  `q` The values from the resulting q_ function of the distribution family.
+#'
+#' @param .n The number of randomly generated points you want.
+#' @param .scale Must be strictly positive.
+#' @param .rate An alternative way to specify the `.scale`
+#' @param .num_sims The number of randomly generated simulations you want.
+#'
+#' @examples
+#' tidy_inverse_exponential()
+#'
+#' @return
+#' A tibble of randomly generated data.
+#'
+#' @export
+#'
+
+tidy_inverse_exponential <- function(.n = 50, .rate = 1, .scale = 1/.rate, .num_sims = 1) {
+
+    # Tidyeval ----
+    n <- as.integer(.n)
+    num_sims <- as.integer(.num_sims)
+    rate <- as.numeric(.rate)
+    scale <- as.numeric(.scale)
+
+    # 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
+            whole number like 50 or 100. It must be greater than 0."
+        )
+    }
+
+    if (!is.numeric(rate) | !is.numeric(scale)){
+        rlang::abort(
+            "The parameters of rate and scale must be of calss numeric."
+        )
+    }
+
+    if (rate <= 0 | scale <= 0){
+        rlang::abort(
+            "The parameters of rate and scale must be strictly positive."
+        )
+    }
+
+    x <- seq(1, num_sims, 1)
+
+    ps <- seq(-n, n - 1, 2)
+    qs <- seq(0, 1, (1 / (n - 1)))
+
+    df <- dplyr::tibble(sim_number = as.factor(x)) %>%
+        dplyr::group_by(sim_number) %>%
+        dplyr::mutate(x = list(1:n)) %>%
+        dplyr::mutate(y = list(actuar::rinvexp(n = n, rate = rate, scale = scale))) %>%
+        dplyr::mutate(d = list(density(unlist(y), n = n)[c("x", "y")] %>%
+                                   purrr::set_names("dx", "dy") %>%
+                                   dplyr::as_tibble())) %>%
+        dplyr::mutate(p = list(actuar::pinvexp(ps, rate = rate, scale = scale))) %>%
+        dplyr::mutate(q = list(actuar::qinvexp(qs, rate = rate, scale = scale))) %>%
+        tidyr::unnest(cols = c(x, y, d, p, q)) %>%
+        dplyr::ungroup()
+
+
+    # Attach descriptive attributes to tibble
+    attr(df, ".rate") <- .rate
+    attr(df, ".scale") <- .scale
+    attr(df, ".n") <- .n
+    attr(df, ".num_sims") <- .num_sims
+    attr(df, "tibble_type") <- "tidy_inverse_exponential"
+    attr(df, "ps") <- ps
+    attr(df, "qs") <- qs
+
+    # Return final result as function output
+    return(df)
+}

R/random-tidy-exponential.R

@@ -1,6 +1,7 @@
 #' Tidy Randomly Generated Exponential Distribution Tibble
 #'
-#' @family Data Generator
+#' @family Continuous Distribution
+#' @family Exponential
 #'
 #' @author Steven P. Sanderson II, MPH
 #'

docs/pkgdown.yml

@@ -3,5 +3,5 @@ pkgdown: 2.0.2
 pkgdown_sha: ~
 articles:
   getting-started: getting-started.html
-last_built: 2022-02-07T20:06Z
+last_built: 2022-02-08T18:02Z