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Re: st: pca and predict--confusion about what it does

From   Nick Cox <>
Subject   Re: st: pca and predict--confusion about what it does
Date   Sat, 20 Oct 2012 23:45:27 +0100

That's (what shall we say) one point of view. Another is that PCA is a
multivariate transformation technique. No model, no estimation. Factor
analysis is a branch of alchemy, so I'll refrain fom comment.

Also, the variances of the PCs are in general not equal, and so are
not entirely a matter of convention.

On Sat, Oct 20, 2012 at 11:35 PM, JVerkuilen (Gmail)
<> wrote:
> On Sat, Oct 20, 2012 at 3:17 PM, Israel Pearce <> wrote:
>> Thank you. I can't seem to find any options on Stata that do not scale
>> the PC's to have mean 0. Do you know of an option that could allow for
>> this or is it not a feature in Stata?
> The location and scale of the set of principal components is
> essentially arbitrary and hence fixed by convention. This isn't all
> that strange, given that the location of residuals in a regression are
> missing. PCA and factor analysis are bilinear regression models that
> make somewhat different assumptions but have the same identification
> issues.
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