Tracking the mean through 100 samples form bivariate uniform distribution ~ unif(0, 1)

bivariate_unif_means_anim.R

library(tidyverse)
library(slider)
library(gganimate)

points <- tibble(
  id = 1:100,
  x = runif(100),
  y = runif(100),
  time = 1:100,
  size = 2,
  color = "black"
)

means <- tibble(
  id = 101,
  x = slide_dbl(points$x, mean, .before = Inf)[-1],
  y = slide_dbl(points$y, mean, .before = Inf)[-1],
  time = 2:100,
  size = 4,
  color = "red"
)


p <- bind_rows(
  points,
  means
) %>% 
  ggplot(aes(x, y, group = id)) +
  geom_hline(aes(yintercept = 0.5), linetype = 2) +
  geom_vline(aes(xintercept = 0.5), linetype = 2) +
  geom_segment(
    aes(x = x1, y = y1, xend = next_x, yend = next_y),
    color = "red",
    alpha = .3,
    data = means %>% 
      mutate(
        next_x = lead(x),
        next_y = lead(y)
      ) %>% 
      rename(x1 = x, y1 = y) %>% 
      mutate(id = row_number()+200)
  ) +
  geom_rug(
    aes(
      color = ifelse(id == 101, "red", "black"),
    )
  ) +
  scale_size_identity() +
  scale_color_identity() +
  geom_point(aes(size = size, color = color)) +
  theme_void() +
  theme(plot.margin = margin(1, 1, 1, 1, "cm")) +
  transition_reveal(time)

animate(p, res = 300, width = 1200, height = 1200)