Hello, I have a matrix with 267 columns, all rows of which have at least one column missing (NA). All three methods i've tried (pcs, princomp, and prcomp) fail with either
"Error in svd(zsmall) : infinite or missing values in 'x'" (latter two) or "Error in cov.wt(z) : 'x' must contain finite values only" The last one happens because of the check if (!all(is.finite(x))) in cov.wt Q: is there a way to do princomp or another method where every row has at least one missing column? I guess if missing values are thrown out, that leaves me with a zero row matrix. I could find the maximal set of columns such that there exists a subset of rows with non NA values for every column in the set - what is an efficient way to do that? Kind Regards JS [[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.