> -----Original Message----- > From: [EMAIL PROTECTED] > [mailto:[EMAIL PROTECTED] On Behalf Of Wittner, Ben > Sent: 02 March 2005 11:33 > To: [EMAIL PROTECTED] > Subject: [R] subset selection for logistic regression > > R-packages leaps and subselect implement various methods of > selecting best or good subsets of predictor variables for > linear regression models, but they do not seem to be > applicable to logistic regression models. > > Does anyone know of software for finding good subsets of > predictor variables for linear regression models? > > Thanks. > > -Ben > > p.s., The leaps package references "Subset Selection in > Regression" by Alan Miller. On page 2 of the 2nd edition of > that text it states the following: > > "All of the models which will be considered in this > monograph will be linear; that is they > will be linear in the regression coefficients.Though most > of the ideas and problems carry > over to the fitting of nonlinear models and generalized > linear models (particularly the fitting > of logistic relationships), the complexity is greatly increased." > > ______________________________________________ > 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 >
The LASSO method and the Least Angle Regression method are two such that have both been implemented (efficiently IMHO - only one least squares for all levels of shrinkage IIRC) in the lars package for R of Hastie and Efron. There is a paper by Madigan and Ridgeway that discusses the use of the Least Angle Regresson approach in the context of logistic regression - available for download from Madigan's space at Ruttgers: www.stat.rutgers.edu/~madigan/PAPERS/lars3.pdf HTH Mike ______________________________________________ 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