Re: [R] Robust PCA?

From: Martin Maechler <>
Date: Fri 19 Jan 2007 - 11:19:40 GMT

>>>>> "BertG" == Bert Gunter <> >>>>> on Thu, 18 Jan 2007 15:28:47 -0800 writes:

    BertG> You seem not to have received a reply.  You can use
    BertG> cov.rob in MASS or cov.Mcd in robustbase or
    BertG> undoubtedly others to obtain a robust covariance
    BertG> matrix and then use that for PCA.

    BertG> Bert Gunter Nonclinical Statistics

Indeed. Thank you Bert.

BTW, (for the archives) do note that their is a "R special interest group" (=: R-SIG) on robust statistics, and mailing list "R-SIG-robust"
(->, also for  archives) with precisely the goal to foster coordinated programming and porting of robust statistics functionality in R.

Expect to see more on this topic there, within the next few days.

Martin Maechler, ETH Zurich

>> -----Original Message----- From:
>> [] On Behalf
>> Of Talbot Katz Sent: Thursday, January 18, 2007 11:44
>> AM To: 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
>> (
>> 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).

>> -- TMK -- 212-460-5430 home 917-656-5351 cell mailing list PLEASE do read the posting guide and provide commented, minimal, self-contained, reproducible code. Received on Fri Jan 19 22:43:00 2007

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