Dear R-users, For the purpose of model selection I am looking for a way to exhaustively (and efficiently) search for best subsets of predictor variables for a logistic regression model. I am looking for something like leaps() but that works with glm. Any feedback highly appreciated. -- Harald von Waldow <hvwaldow at chem.ethz.ch> Safety and Environmental Technology Group Institute for Chemical and Bioengineering Swiss Federal Institute of Technology Zurich Fon: +41 44 632 7142 Fax: +41 44 632 1189 Web: www.sust-chem.ethz.ch
Harald von Waldow wrote:> > For the purpose of model selection I am looking for a way to > exhaustively (and efficiently) search for best subsets of predictor > variables for a logistic regression model. >Of all the dangerous ways of doing this and getting confusing results, gl1ce in lasso2 should be the least risky. Dieter -- View this message in context: http://www.nabble.com/all-subsets-for-glm-tp22850382p22851112.html Sent from the R help mailing list archive at Nabble.com.
> Of all the dangerous ways of doing this and getting confusing results, > gl1ce in lasso2 should be the least risky.Thanks Dieter. In case an exhaustive search (all subsets) remains infeasible, I'll include a shrinkage method for sure. Looks like glmpath could be useful here. Best, Harald