Looks like my post might get some problems, so I re-wrote my question plus some new one...
I noticed that the points on the biplot are not exactly the same as the predicted values. Another relevant question: should I expect that all the vector points have the same length if chose parameters of "cor=T ", for example, pca2=princomp((data), cor=T)? Could any body give me a hint about any of these questions? Thanks. ________________________________ To: Jim Lemon <j...@bitwrit.com.au> Cc: "r-help@r-project.org" <r-help@r-project.org> Sent: Tuesday, April 30, 2013 9:51 AM Subject: Re: [R] biplot for principal componens analysis very helpful!! Thanks a lot. ________________________________ From: Jim Lemon <j...@bitwrit.com.au> Cc: "r-help@r-project.org" <r-help@r-project.org> Sent: Monday, April 29, 2013 6:53 PM Subject: Re: [R] biplot for principal componens analysis On 04/30/2013 08:24 AM, capricy gao wrote: > > > I did a PCA for my data which has a dimension of 19000X4 using princomp >> pca2=princomp((data), cor=F) > > > > > > and obtained a biplot with 19000 labels which were very busy. How can I just > show 19000 spot w/o labels? >> biplot(pca2) > Hi capricy, I suppose you could try: biplot(pca2,xlabs=rep(".",19000)) Jim [[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. [[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.