Re: [R] how to test robustness of correlation

From: Berton Gunter <gunter.berton_at_gene.com>
Date: Thu 26 Jan 2006 - 07:57:47 EST


check out cov.rob() in MASS (among others, I'm sure). The procedure is far more sophisticated than "outlier removal" or resampling (??). References are given in the docs.

"The business of the statistician is to catalyze the scientific learning process." - George E. P. Box    

> -----Original Message-----
> From: r-help-bounces@stat.math.ethz.ch
> [mailto:r-help-bounces@stat.math.ethz.ch] On Behalf Of
> yang.x.qiu@gsk.com
> Sent: Wednesday, January 25, 2006 12:37 PM
> To: r-help@stat.math.ethz.ch
> Subject: [R] how to test robustness of correlation
>
> Hi, there:
>
> As you all know, correlation is not a very robust procedure.
> Sometimes
> correlation could be driven by a few outliers. There are a
> few ways to
> improve the robustness of correlation (pearson correlation),
> either by
> outlier removal procedure, or resampling technique.
>
> I am wondering if there is any R package or R code that have
> incorporated
> outlier removal or resampling procedure in calculating correlation
> coefficient.
>
> Your help is greatly appreciated.
>
> Thanks.
> Yang
>
> Yang Qiu
> Integrated Data Analysis
> Cheminformatics@RTP
> GlaxoSmithKline
> [[alternative HTML version deleted]]
>
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R-help@stat.math.ethz.ch mailing list
https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Thu Jan 26 08:04:31 2006

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