the variance is the eigen values of the correlation matrix of yoru matrix X.cor <- cor(X) X.e <- eigen(X.cor) X.e$values# Eigenvalues of cor(X) = variances you're asking about
kayj wrote: > > Hi All, > > I performed an svd on a matrix X and saved the first three column of the > left singular matrix U. ( I assume that they correspond to the projection > of the matrix on the first three eigen vectors that corresponds to the > first three largest eigenvalues). I would like to know how much variance > is explained by the first eigenvectors? how can I find that. > > Thanks for your help > ----- Yasir H. Kaheil Catchment Research Facility The University of Western Ontario -- View this message in context: http://www.nabble.com/SVD-on-a-matix-tp17441337p17455129.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.
