Hi, I have R code like so:
num.columns.back.since.last.occurence <- function(m, outcome) { nrows <- dim(m)[1]; ncols <- dim(m)[2]; res <- matrix(rep.int(0, nrows*ncols), nrow=nrows); for(row in 1:nrows) { for(col in 2:ncols) { res[row,col] <- if(m[row,col-1]==outcome) {0} else {1+res[row,col-1]} } } res; } but on the very large matrices I apply this the execution times are a problem. I would appreciate any help to rewrite this with more "standard"/native R functions to speed things up. -- View this message in context: http://r.789695.n4.nabble.com/Speeding-up-accumulation-code-in-large-matrix-calc-tp4417911p4417911.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.