The PCs that are associated with the smaller eigenvalues. ---------------------------------------------------------------------------- -------
Ravi Varadhan, Ph.D. Assistant Professor, The Center on Aging and Health Division of Geriatric Medicine and Gerontology Johns Hopkins University Ph: (410) 502-2619 Fax: (410) 614-9625 Email: [EMAIL PROTECTED] Webpage: http://www.jhsph.edu/agingandhealth/People/Faculty/Varadhan.html ---------------------------------------------------------------------------- -------- -----Original Message----- From: Patrick Connolly [mailto:[EMAIL PROTECTED] Sent: Monday, July 02, 2007 4:23 PM To: Ravi Varadhan Cc: 'Mark Difford'; r-help@stat.math.ethz.ch Subject: Re: [R] Question about PCA with prcomp On Mon, 02-Jul-2007 at 03:16PM -0400, Ravi Varadhan wrote: |> Mark, |> |> What you are referring to deals with the selection of covariates, since PC |> doesn't do dimensionality reduction in the sense of covariate selection. |> But what Mark is asking for is to identify how much each data point |> contributes to individual PCs. I don't think that Mark's query makes much |> sense, unless he meant to ask: which individuals have high/low scores on |> PC1/PC2. Here are some comments that may be tangentially related to Mark's |> question: |> |> 1. If one is worried about a few data points contributing heavily to the |> estimation of PCs, then one can use robust PCA, for example, using robust |> covariance matrices. MASS has some tools for this. |> 2. The "biplot" for the first 2 PCs can give some insights |> 3. PCs, especially, the last few PCs, can be used to identify "outliers". What is meant by "last few PCs"? -- ~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~. ___ Patrick Connolly {~._.~} Great minds discuss ideas _( Y )_ Middle minds discuss events (:_~*~_:) Small minds discuss people (_)-(_) ..... Anon ~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~.~. ______________________________________________ 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.