[R] PCA problem in R

[Berton Gunter]

To add to Brian Ripley's note:

All but possibly the first few (1-3, say) PC's are very likely  random
numbers. You need to either consult references or get statistical help to
understand why. May I also suggest that you add Prof Ripley's book on
PATTERN RECOGNITION AND NEURAL NETWORKS to your reading list -- in
particular, Ch. 9.

-- Bert Gunter
Genentech Non-Clinical Statistics
South San Francisco, CA
 
"The business of the statistician is to catalyze the scientific learning
process."  - George E. P. Box
 
 

> -----Original Message-----
> From: r-help-bounces at stat.math.ethz.ch 
> [mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Prof 
> Brian Ripley
> Sent: Saturday, August 13, 2005 11:26 PM
> To: Alan Zhao
> Cc: r-help at stat.math.ethz.ch
> Subject: Re: [R] PCA problem in R
> 
> On Sat, 13 Aug 2005, Alan Zhao wrote:
> 
> > When I have more variables than units, say a 195*10896 
> matrix which has
> > 10896 variables and 195 samples. prcomp will give only 195 principal
> > components. I checked in the help, but there is no 
> explanation that why
> > this happen.
> 
> There is not even a definition of a PC in the help. Did you read the 
> references?  This is what they are given for!
> 
> > Can we get more than 195 PCs for this case? Thank you very
> > much.
> 
> Check out the theory in the references.  You can, but all the 
> remaining 
> ones are constant across samples and not uniquely defined.  
> You are likely 
> to have trouble storing the coefficients (10701x10896 is 800Mb).
> It would be better to do whatever you intend to do with them without 
> explicitly computing them.
> 
> -- 
> Brian D. Ripley,                  ripley at 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 272866 (PA)
> Oxford OX1 3TG, UK                Fax:  +44 1865 272595
> 
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