max and min functions that are similar to colMeans

Question

I am wondering if there are high speed min and max function that works on columns similarly to colMeans?

For 'max', although I can simulate the behavior with 'apply' such as the following:

colMax <- function (colData) {
    apply(colData, MARGIN=c(2), max)
}

It seems a lot slower than the colMeans in the base package.

Answer 1

pmax is ~ 10x faster than apply. Still not as fast as colMeans though.

data = matrix(rnorm(10^6), 100)
data.df = data.frame(t(data))

system.time(apply(data, MARGIN=c(2), max))
system.time(do.call(pmax, data.df))
system.time(colMeans(data))

> system.time(apply(data, MARGIN=c(2), max))
   user  system elapsed 
  0.133   0.006   0.139 
> system.time(do.call(pmax, data.df))
   user  system elapsed 
  0.013   0.000   0.013 
> system.time(colMeans(data))
   user  system elapsed 
  0.003   0.000   0.002