[R] Efficient calculation of matrix cumulative standard deviation

[Abiel Reinhart]

I am trying to calculate the cumulative standard deviation of a
matrix. I want a function that accepts a matrix and returns a matrix
of the same size where output cell (i,j) is set to the standard
deviation of input column j between rows 1 and i. NAs should be
ignored, unless cell (i,j) of the input matrix itself is NA, in which
case cell (i,j) of the output matrix should also be NA.

I could not find a built-in function, so I implemented the following
code. Unfortunately, this uses a loop that ends up being somewhat slow
for large matrices. Is there a faster built-in function or can someone
suggest a better approach?

***CODE***

cumsd <- function(mat)
{
	retval <- mat*NA
	for (i in 2:nrow(mat)) retval[i,] <- sd(mat[1:i,], na.rm=T)
	retval[is.na(mat)] <- NA
	retval
}

Thanks.