Re: [R] Robust PCA?

From: Bert Gunter <gunter.berton_at_gene.com>
Date: Thu 18 Jan 2007 - 23:28:47 GMT


You seem not to have received a reply.

You can use cov.rob in MASS or cov.Mcd in robustbase or undoubtedly others to obtain a robust covariance matrix and then use that for PCA.

Bert Gunter
Nonclinical Statistics
7-7374

-----Original Message-----
From: r-help-bounces@stat.math.ethz.ch
[mailto:r-help-bounces@stat.math.ethz.ch] On Behalf Of Talbot Katz Sent: Thursday, January 18, 2007 11:44 AM To: r-help@stat.math.ethz.ch
Subject: [R] Robust PCA?

Hi.

I'm checking into robust methods for principal components analysis. There seem to be several floating around. I'm currently focusing my attention on a method of Hubert, Rousseeuw, and Vanden Branden (http://wis.kuleuven.be/stat/Papers/robpca.pdf) mainly because I'm familiar with other work by Rousseeuw and Hubert in robust methodologies. Of course,

I'd like to obtain code for this method, or another good robust PCA method, if there's one out there. I haven't noticed the existence on CRAN of a package for robust PCA (the authors of the ROBPCA method do provide MATLAB code).


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