plyr_example3.R

d <- expand.grid(n=c(3,5,10,20), type=c("normal","t"))
d <- d[rep(seq_len(nrow(d)),each=nrep),]

simulate <- function(n, type) {
  if (type == "normal") {
    dat <- rnorm(n)
  } else {
      dat <- rt(n, df=3)
    }
  dat
  meanerr <- abs(mean(dat) - 0)
  medianerr <- abs(median(dat) - 0)
  c(mean=meanerr, median=medianerr)
}

library(plyr)

# mdply does everything: takes columns of d as multivariate input
# to simulate() and then adds the output as columns to d
d2 <- mdply(d, simulate)

d2$n <- factor(d2$n)

library(reshape)
m <- melt(d2, id.vars=c("n","type"))

library(ggplot2)
ggplot(m, aes(x=n, y=value, col=variable)) + geom_boxplot() +
  facet_wrap(~ type) + ylim(0,2)