I\'ve been trying to use ggplot2 to produce a plot similar to this R graphic:
xv<-seq(0,4,0.01)
yv<-dnorm(xv,2,0.5)
plot(xv,yv,type=\"l\")
polygon(c(
This is essentially a copy of Luciano's answer which I found useful, however it may save some time for others wanting to use this approach.
Create the data. Here the density at 0.001 intervals from the 0.1th percentile to the 99.9th percentile of a normal distribution with specified mean and sd.
mean_ = 10
sd_ = 4
x = seq(qnorm(c(0.001), mean_, sd_),qnorm(c(0.999), mean_, sd_),0.001)
distdata = data.frame(x=x,y=dnorm(x,mean_,sd_))
A function for shading left or right tails from specific values.
shade_under_curve = function(p, d, left=NULL, right=NULL, distrib, fill, ...){
if(!is.null(left)){
shade = rbind(c(d[1, "x"], 0), d[d$xright,], c(d[nrow(d), "x"], 0))
}
value = c(left, right)
ytop<-distrib(value,...)
p + geom_segment(aes(x=value,y=0,xend=value,yend=ytop)) +
geom_polygon(data = shade, aes(x, y), alpha=0.2, fill=fill)
}
Examples:
p = qplot(x=distdata$x,y=distdata$y,geom="line")
shade_under_curve(p, distdata, left=3, distrib=dnorm, mean=mean_, sd=sd_, fill = "red")
shade_under_curve(p, distdata, right=15, distrib=dnorm, mean=mean_, sd=sd_, fill = "blue")
p2 = shade_under_curve(p, distdata, left=qnorm(0.025, mean_, sd_), distrib=dnorm, mean=mean_, sd=sd_, fill = "green")
shade_under_curve(p2, distdata, right=qnorm(0.975, mean_, sd_), distrib=dnorm, mean=mean_, sd=sd_, fill = "green")