[R] Question about PCA with prcomp

Patrick Connolly p_connolly at ihug.co.nz
Mon Jul 2 22:22:31 CEST 2007

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   
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