For quadratic penalization (generalization of ridge regression) the lrm function in the rms package supports this. See also the rms pentrace function.
Frank djmuseR wrote: > > Hi: > > glmnet is a good place to start. > > HTH, > Dennis > > On Tue, Jun 21, 2011 at 12:01 AM, Markku Karhunen > <markku.karhu...@helsinki.fi> wrote: >> >> Hi Community, >> >> I would like to do regularized logistic regression, e.g. lasso, plasso or >> ridge regression. Can you recommend any packages? Low memory requirement >> / >> computational cheapness would be a plus. >> >> Markku Karhunen >> Uni. Helsinki >> >> ______________________________________________ >> R-help@r-project.org mailing list >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide >> http://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code. >> > > ______________________________________________ > R-help@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. > ----- Frank Harrell Department of Biostatistics, Vanderbilt University -- View this message in context: http://r.789695.n4.nabble.com/Regularized-logistic-regression-tp3613537p3615373.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.