Hello List, I was wondering if a package or piece of code exists that will allow all possible subsets regression model selection within program R. I have already looked at step(AIC) which does not test differing combinations of variables within a model as far as I can tell. In addition I tried to use the leaps command, but that does not use the criterion I am looking for. Any help or advice would be greatly appreciated. Thanks Matt Williamson Matthew Williamson Graduate Research Assistant Department of Fishery and Wildlife Biology Colorado State University, Fort Collins, CO 80523 Office: (970)491-5790 Cell:(970)412-0442 <><><><><><><><><><><><><><><><><><> "We are now confronted by the fact...that wars are no longer won;...all wars are lost by all who wage them; the only difference between participants is the degree and kind of losses they sustain. ...Science has so sharpened the fighter's sword that it is impossible for him to cut his enemy without cutting himself." --Aldo Leopold [[alternative HTML version deleted]]
On Tue, 3 Jan 2006, Matt Williamson wrote:> Hello List, > I was wondering if a package or piece of code exists that will allow all > possible subsets regression model selection within program R. I have > already looked at step(AIC) which does not test differing combinations > of variables within a model as far as I can tell. In addition I tried > to use the leaps command, but that does not use the criterion I am > looking for.leaps() or regsubsets() in the leaps package almost certainly do use the criterion you are looking for (even though you don't tell us what that criterion is). These functions produce one or more best models of each size, and for models of the same size all the commonly-used criteria reduce to ranking by residual sum of squares, which is what leaps() and regsubsets() do. -thomas Thomas Lumley Assoc. Professor, Biostatistics tlumley at u.washington.edu University of Washington, Seattle