I like Kjetil's suggestion of a shrinkage estimator. Perhaps this would be a good time to experiment with Trevor Hastie's 'lars' package.
If you have a lot of correlated inputs I might suggest using Andy Liaw's randomforest package. I have found this technique to be very valuable in this setting. The partial dependency plots are a good way to explore the functional relationships of the variables. --Matt -----Original Message----- From: [EMAIL PROTECTED] [mailto:[EMAIL PROTECTED] Behalf Of Kjetil Brinchmann Halvorsen Sent: Tuesday, October 12, 2004 17:16 PM To: Ian Fiske Cc: [EMAIL PROTECTED] Subject: Re: [R] covariate selection? Ian Fiske wrote: > Hello, > > I am hoping someone can help me with the following multivariate > issue: I have a model consisting of about 50 covariates. I would > like to reduce this to about 5 covariate for the reduced model by > combining cofactors that are strongly correlated. Is there a package > or function that would help me with this in R? I appreciate any > suggestions. > > Thanks, > Ian > > ______________________________________________ > [EMAIL PROTECTED] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! > http://www.R-project.org/posting-guide.html > > have a look at package leaps, and also consider ridge regression. -- Kjetil Halvorsen. Peace is the most effective weapon of mass construction. -- Mahdi Elmandjra ______________________________________________ [EMAIL PROTECTED] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html ______________________________________________ [EMAIL PROTECTED] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html