Efficient calculation of matrix cumulative standard deviation in r

Question

I recently posted this question on the r-help mailing list but got no answers, so I thought I would post it here as well and see if there were any suggestions.

I am

Answer 1

Another try (Marek's is faster)

cumsd2 <- function(y) {
n <- nrow(y)
apply(y,2,function(i) {
    Xmeans <- lapply(1:n,function(z) rep(sum(i[1:z])/z,z))
    Xs <- sapply(1:n, function(z) i[1:z])
    sapply(2:n,function(z) sqrt(sum((Xs[[z]]-Xmeans[[z]])^2,na.rm = T)/(z-1)))
})
}