From Prof Brian Ripley <ripley@stats.ox.ac.uk>  Wed Feb  2 14:37:29 2000
From: Prof Brian Ripley <ripley@stats.ox.ac.uk> (Prof Brian Ripley)
Date: Wed, 2 Feb 2000 14:37:29 +0000 (GMT)
Subject: [Rd] Feature requests for princomp(.) : Allow cor() specifications
Message-ID: <200002021437.OAA14274@toucan.stats.ox.ac.uk>

> From: Martin Maechler <maechler@stat.math.ethz.ch>
> Date: Mon, 31 Jan 2000 16:21:10 +0100 (MET)
> 
> (all in subject).
> 

Having you been looking at your S-PLUS recently?

> If I want to do a PC analysis in a situation with missing data,
> I may want to have same flexibility as with "cor(.)",
> e.g., I may want
> 
>       princomp(x, ...,  use.obs = "pairwise.complete")

Um. That's a way not to get a valid covariance matrix and hence no
valid PCA.

> Actually, I may want even more flexibility.
> Currently,
> 	princomp(.) 
> has
> 
>     if (cor) 
>         cv <- get("cor", envir = .GlobalEnv)(z)
>     else cv <- cov(z)
>     edc <- eigen(cv)
> 
> and If may want it to use a robust covariance or correlation matrix instead,
> e.g.,
> 
>     princomp(x, cv = cov.mve(x), .....)

as in

princomp(x, data = NULL, covlist = NULL, weights = NULL, scores = T, cor = F, 
        na.action, subset)
?

> Note that for prcomp() which works on the SVD rather than the
> correlation/cov. matrix,  similar flexibility may be required.
> 
> Opinions?
> Volunteers?
> 
> (either one is sufficient to answer!)
> 

It really is easy.  If there were not a feature freeze on I would do
it right now.

-- 
Brian D. Ripley,                  ripley@stats.ox.ac.uk
Professor of Applied Statistics,  http://www.stats.ox.ac.uk/~ripley/
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272860 (secr)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

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[Rd] Feature requests for princomp(.) : Allow cor() specifications
Prof Brian Ripley