Question

I’d like to superpose a histogram and an xyplot representing the cumulative distribution function using r’s lattice package.

I’ve tried to accomplish this with custom panel functions, but can’t seem to get it right–I’m getting hung up on one plot being univariate and one being bivariate I think.

Here’s an example with the two plots I want stacked vertically:

set.seed(1)
x <- rnorm(100, 0, 1)

discrete.cdf <- function(x, decreasing=FALSE){
    x <- x[order(x,decreasing=FALSE)]
    result <- data.frame(rank=1:length(x),x=x)
    result$cdf <- result$rank/nrow(result)
    return(result)
}

my.df <- discrete.cdf(x)

chart.hist <- histogram(~x, data=my.df, xlab="")
chart.cdf <- xyplot(100*cdf~x, data=my.df, type="s",
                    ylab="Cumulative Percent of Total")

graphics.off()
trellis.device(width = 6, height = 8)
print(chart.hist, split = c(1,1,1,2), more = TRUE)
print(chart.cdf, split = c(1,2,1,2))

I’d like these superposed in the same frame, rather than stacked.

The following code doesn’t work, nor do any of the simple variations of it that I have tried:

xyplot(cdf~x,data=cdf,
          panel=function(...){
              panel.xyplot(...)
              panel.histogram(~x)
          })

Answer 1

You were on the right track with your custom panel function. The trick is passing the correct arguments to the panel.– functions. For panel.histogram, this means not passing a formula and supplying an appropriate value to the breaks argument:

EDIT Proper percent values on y-axis and type of plots

xyplot(100*cdf~x,data=my.df,
          panel=function(...){
              panel.histogram(..., breaks = do.breaks(range(x), nint = 8),
                type = "percent")
              panel.xyplot(..., type = "s")
          })