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: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of > [EMAIL PROTECTED] > 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 > [EMAIL PROTECTED] > GlaxoSmithKline > [[alternative HTML version deleted]] > > ______________________________________________ > 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 > ______________________________________________ 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
