stat_function
is designed to overlay the same function in every panel. (There’s no obvious way to match up the parameters of the function with the different panels).
As Ian suggests, the best way is to generate the normal curves yourself, and plot them as a separate dataset (this is where you were going wrong before – merging just doesn’t make sense for this example and if you look carefully you’ll see that’s why you’re getting the strange sawtooth pattern).
Here’s how I’d go about solving the problem:
dd <- data.frame(
predicted = rnorm(72, mean = 2, sd = 2),
state = rep(c("A", "B", "C"), each = 24)
)
grid <- with(dd, seq(min(predicted), max(predicted), length = 100))
normaldens <- ddply(dd, "state", function(df) {
data.frame(
predicted = grid,
density = dnorm(grid, mean(df$predicted), sd(df$predicted))
)
})
ggplot(dd, aes(predicted)) +
geom_density() +
geom_line(aes(y = density), data = normaldens, colour = "red") +
facet_wrap(~ state)