hope this helps. spencer graves
Liaw, Andy wrote:
In the `Detail' section of ?princomp:
princomp only handles so-called Q-mode PCA, that is feature extraction of
variables. If a data matrix is supplied (possibly via a formula) it is
required that there are at least as many units as variables. For R-mode PCA
use prcomp.
Andy
-----Original Message-----
From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] Sent: Thursday, October 16, 2003 5:14 AM
To: [EMAIL PROTECTED]
Subject: [R] princomp with more coloumns than rows: why not?
As of R 1.7.0, princomp no longer accept matrices with more coloumns than rows. I'm curious: Why was this decision made?
I work a lot with data where more coloumns than rows is more of a rule than an exception (for instance spectroscopic data). To me, princomp have two advantages above prcomp: 1) It has a predict method, and 2) it has a biplot method.
A biplot method shouldn't be too difficult to implement (I believe I've seen one on R-help).
A predict method seems to be more difficult, because the prcomp object doesn't include the means that need to be subtracted from the new data. Would it break conformance with S to let prcomp return the means as well?
-- Sincerely, Bjørn-Helge Mevik
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