In JamesHWade/shinydist: Explore Distributions with Shiny

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

library(shinydist)
ggplot2::theme_set(cowplot::theme_cowplot())

Normal Distribution

The normal distribution

n_obs <- 500
mean <- 0
sd <- 2

cat("# Copy this code:\nrnorm(", n_obs, ", mean = ", mean, ", sd = ", sd, ")", sep = "")

norm_dist <- tibble::tibble(
  obs   = seq_along(n_obs),
  value = rnorm(n_obs, mean = 0, sd = 2),
  distribution = "normal"
)

plot_dist <- function(tbl) {
  ggplot2::ggplot(tbl) +
    ggplot2::aes(x = value,
                 color = distribution,
                 fill = ggplot2::after_scale(ggplot2::alpha(color, 0.6))) +
    ggplot2::geom_histogram(bins = n_obs / 10)
}

plot_dist(norm_dist)

Gamma Distribution

n_obs <- 500
shape <- 5
scale <- 1

mean <- shape * scale
variance <- shape * scale^2

cat("Gamma Distribution\nmean: ", mean, ", variance: ", variance,
    "\n# Copy this code:\nrgamma(", n_obs, ", shape = ", shape, ", scale = ", scale, ")", sep = "")

gamma_dist <- tibble::tibble(
  obs   = seq_along(n_obs),
  value = rgamma(n_obs, shape = shape, scale = scale),
  distribution = "gamma"
)

plot_dist(gamma_dist)