Hi Everyone, Given the scenario I have, I was wondering if anyone would be able to give me a hind on how to get the results from hubers() in a more efficient way.
I have an outcome on an array [N x S x D]. I also have a factor (levels 1,2,3) stored on a matrix N x S. My objective is to get "mu" and "sigma" for each of the N rows (outcome) stratified by the factor (levels 1, 2 and 3) for each of the D "levels", but using MASS:hubers(). Ideally the final result would be an array [N x D x 3 x 2]. The following toy example demonstrates what I want to do, and I'd like to improve the performance when working on my case, where S=400 and N > 200000 Thank you very much for any suggestion. benilton ## begin toy example set.seed(1) N <- 100 S <- 5 D <- 2 outcome <- array(rnorm(N*S*D), dim=c(N, S, D)) classes <- matrix(sample(c(1:3, NA), N*S, rep=T), ncol=S) results <- array(NA, dim=c(N, D, 3, 2)) library(MASS) myHubers <- function(x) if (length(x)>1) as.numeric(hubers(x)) else c(NA, NA) for (n in 1:N) for (d in 1:D){ tmp <- outcome[n,,d] grp <- classes[n,] results[n, d,,] <- t(sapply(split(tmp, factor(grp, levels=1:3)), myHubers)) } ## end -- Benilton Carvalho PhD Candidate Department of Biostatistics Johns Hopkins University ______________________________________________ R-help@stat.math.ethz.ch 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.