Dear R gurus, to compute the correlation matrix of "n" variables with "n_obs" observations each, possibly including NA, I use cor(M, use="pairwise.obs") where m is a "n" x "nobs" matrix.
Now I want to know the number of observations actually used in this computation, namely for each pair of columns in M, say pair (i,j), I want to compute sum( !is.na(M[,i]) & !is.na(M[,j]) ). I can think of several ways of constructing all pairs (i,j) with i<j, then computing the sum above, but for n=2000 and nobs=700 the computation time is prohibitive. Is there an efficient way to solve this? Many thanks, jc [[alternative HTML version deleted]] ______________________________________________ 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.