Animations for Unif(0,1) estimators of central tendency

anim_estimators_unif.R

library(tidyverse)
library(gganimate)

sample_size <- seq(5, 30, by=5)

create_data <- function(sample_size){
  tibble(ss=sample_size, n=1:1e6, x=map(n, ~runif(sample_size))) %>%
  mutate(mean = map_dbl(x, mean),
         median = map_dbl(x, median),
         range = map_dbl(x, ~(max(.x) - min(.x))/2)) %>%
  pivot_longer(cols=mean:range) %>%
  select(-x)
}

df <- map_dfr(sample_size, ~create_data(.x))

anim <-
df %>%
  ggplot(aes(x=value, fill=name, color=name)) +
  geom_density(alpha=0.3) +
  scale_fill_manual(name = "Estimator",
                    labels = c("Mean", "Median", "Midrange"),
                    values = c("#1b9e77", "#d95f02", "#7570b3")) +
  scale_color_manual(name = "Estimator",
                     labels = c("Mean", "Median", "Midrange"),
                     values = c("#1b9e77", "#d95f02", "#7570b3")) +
  labs(subtitle = "Sample Size: {closest_state}",
       title = "Estimators of central tendency for Unif(0,1)",
       x= "x",
       y= "Probability Density (KDE)",
       caption = "Distributions estimated by Monte Carlo simulation") +
  cowplot::theme_cowplot(font_family = "Source Sans Pro",
                         font_size = 10) +
  theme(plot.title = element_text(size=10),
        legend.position = c(0.8,0.8)) +
  transition_states(ss, state_length = 1, transition_length = 2) +
  ease_aes('quartic-in-out')

# Render animation
out <- animate(anim,
               duration=10,
               fps=60,
               height = 3,
               width = 4,
               units = "in",
               res = 300,
               renderer = ffmpeg_renderer())

# Save to mp4
anim_save(animation = out, filename = "unif_center_anim.mp4")