Plotting posterior predictive density

ppd_plot.R

library(ggplot2); library(dplyr)

aa <- data_frame(a = rnorm(30, 2, .1), b = rnorm(30, .5, .05), sigma = rnorm(30, 1, .1)) 
g <- ggplot(data.frame(x = c(-1, 5.5)), aes(x))
for(i in 1:nrow(aa)) {
 g <- g +
  stat_function(fun = dnorm, args = list(mean = c(aa$a[i] + aa$b[i]), sd = aa$sigma[i]), alpha = 0.3)  
}
 
g +
  geom_linerange(data = data.frame(ymin = 0, ymax = max(dnorm(1, aa$a + aa$b, aa$sigma)), x = 1), aes(x= x, ymin = ymin, ymax = ymax)) +
  geom_point(data= data.frame(x = rep(1, nrow(aa) +1), y = c(0, dnorm(1, aa$a + aa$b, aa$sigma))), aes(x = x, y = y), colour = "red") +
  xlab("y") +
  ylab("Density") +
  ggtitle("We can evaluate at the actual outcome\nover posterior draws", subtitle = "f(y | x, a, b, s)")