I'm looking for someone to explain the difference between these procedures. The function prcomp() does principal components anaylsis, and the function cmdscale() does classical multi-dimensional scaling (also called principal coordinates analysis).
My confusion stems from the fact that they give very similar results: my.d <- matrix(rnorm(50), ncol=5) rownames(my.d) <- paste("c", 1:10, sep="") # prcomp prc <- prcomp(my.d) # cmdscale mds <- cmdscale(dist(my.d)) cor(prc$x[,1], mds[,1]) # produces 1 or -1 cor(prc$x[,2], mds[,2]) # produces 1 or -1 Presumably, under the defaults for these commands in R, they carry out the same (or very similar) procedures? Thanks Mick The information contained in this message may be confidentia...{{dropped}} ______________________________________________ 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.