Dear All, Could someone please give some advice the way to do linear modelling via best subset regression in R? I'd really appreciate for your kindness. Thanks, Kagba [[alternative HTML version deleted]]
On 4 May 2011 09:47, FMH <kagba2006 at yahoo.com> wrote:> Dear All, > > Could someone please give some advice the way to do linear modelling via best subset regression in R? I'd really appreciate for your kindness. >Google is your friend here: http://www.google.com/search?q=best+subsets+regression+R , and sends me to this page: http://www.statmethods.net/stats/regression.html Jeremy -- Jeremy Miles Support Dan and Alex's school: Vote for Goethe Charter School to receive a grant from Pepsi to help build a library: http://www.refresheverything.com/gicslibrary
Beware - this approach is a statistical train wreck. Been there, done that. If all you want is "an" answer it will save you a lot of time thinking, however. Frank FMH-4 wrote:> > Dear All, > ? > Could someone please give some advice the way to do linear modelling via > best subset regression in R? I'd really appreciate for your kindness. > ? > Thanks, > Kagba > [[alternative HTML version deleted]] > > > ______________________________________________ > R-help at 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/best-subset-regression-in-R-tp3496671p3496981.html Sent from the R help mailing list archive at Nabble.com.
On Wed, May 4, 2011 at 9:47 AM, FMH <kagba2006 at yahoo.com> wrote:> Dear All, > > Could someone please give some advice the way to do linear modelling via best subset regression in R?...Yes. Don't do it. -- Bert (Very Brief Explanation: Best subset regression was a questionable approach to parsimonious modeling largely dictated by the statistical/computing technology available in the 1960's and 70's. It should by now be abandoned, buried, and forgotten. Use shrinkage instead. LARS/LASSO (in the glmnet package) are among the possibilities. Consult your local statistician for help (after making sure he/she knows about such approaches, as not all do). Frank Harrell's "Regresiion Modeling Strategies" is a useful starting point to learn about this.> > Thanks, > Kagba > ? ? ? ?[[alternative HTML version deleted]] > > > ______________________________________________ > R-help at 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. > >-- "Men by nature long to get on to the ultimate truths, and will often be impatient with elementary studies or fight shy of them. If it were possible to reach the ultimate truths without the elementary studies usually prefixed to them, these would not be preparatory studies but superfluous diversions." -- Maimonides (1135-1204) Bert Gunter Genentech Nonclinical Biostatistics