Adding an arbitrary function to a ggplot histogram

Question

Context: I have some data, and I wish to:

plot a histogram of them
add a kernel density
add a "theoretical density"
add a legend to distinguish between 2. and 3.

Consider:

X <- rnorm(1000,0,1)
Y <- (X^2-1)/2
ggplot(as.data.frame(Y), aes(x=Y)) + 
    geom_histogram(aes(y=..density..),      
                   binwidth=.2,
                   colour="black", fill="white") +
    geom_density(alpha=.2, fill="#FF6666")

enter image description here

This accomplishes 1. and 2., but how can I achieve 3. and 4.? I have written the function I wish to plot:

myfunc <- function(x) {
    2*exp(-x-0.5)/(sqrt(2*x+1)*sqrt(2*pi))
}

Any other comments/critiques are welcome (I am learning)

For (3) see stat_function, though the legend might require calculating both lines outside of ggplot and adding a geom_path layer manually, depending on how picky you are about the legend appearance. — joran
– joran, Commented Oct 13, 2012 at 23:45

joran · Accepted Answer · 2012-10-18 13:58:01Z

Your custom function isn't terribly well behaved on that domain, so I substituted another simple one in, for illustration purposes.

#Dummy data set for the legend
dat <- data.frame(x = rep(NA_integer_,2),
                  y = rep(NA_integer_,2),
                  grp = c('Theoretical','Estimated'))
ggplot(as.data.frame(Y), aes(x=Y)) + 
    geom_histogram(aes(y=..density..),      
                   binwidth=.2,
                   colour="black", fill="white") +
    geom_density(alpha=.2, fill="#FF6666",color = '#FF6666') + 
    stat_function(fun = function(x) exp(-x),colour = "blue") + 
    geom_point(data = dat,aes(x = x,y = y,color = grp)) + 
    scale_color_manual(name = "",values = c('#FF6666','blue'))

enter image description here

I monkeyed with the colors somewhat, but you can tweak that as you see fit. There may be a cleaner way to do the legend, but the "data frame with NA's and a grouping variable" is sort of my standard method for this kind of thing.

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