Hi, Say x.train is a matrix of covariates that I want to do PCA on, so I can do regression on its principal components, and x.test is a test set of the same covariates on which I want to evaluate the regression fit. I would like the covariates to be centred and scaled:
p <- prcomp(x.train, center=TRUE, scale=TRUE) x.train.pc <- predict(p) Now I want to get the PCs from the test set. Should I use the same center and scale vectors from the training set: x.test.pc <- predict(p, newdata=x.test, center=p$center, scale=p$center) or use the training set's own centers and scales: x.test.pc <- predict(p, newdata=x.test, center=TRUE, scale=TRUE) Thanks, Gad -- Gad Abraham Dept. CSSE and NICTA The University of Melbourne Parkville 3010, Victoria, Australia email: [EMAIL PROTECTED] web: http://www.csse.unimelb.edu.au/~gabraham ______________________________________________ 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.
