[R] how to test robustness of correlation

Berton Gunter gunter.berton at gene.com
Wed Jan 25 21:57:47 CET 2006

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.

-- 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 
> yang.x.qiu at gsk.com
> Sent: Wednesday, January 25, 2006 12:37 PM
> To: r-help at 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 at RTP
> GlaxoSmithKline
> 	[[alternative HTML version deleted]]
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