On Sat, Jun 2, 2012 at 3:19 AM, farmedgirl <ksteinm...@cdpr.ca.gov> wrote: > Hi > i need to create a model from 250 + variables with high collinearity, and > only 17 data points (p = 250, n = 750). I would prefer to use Cp, AIC, > and/or BIC to narrow down the number of variables, and then use VIF to > choose a model without collinearity (if possible). I realize that having a > huge p and small n is going to give me extreme linear dependency problems, > but I *think* these model selection criteria should still be useful? > > I have currently been running regsubsets for over a week with no results. I > have no idea if R is still working, or if the computer is hung. I ran > regsubsets on a smaller portion of the data, also with linear dependency > problems, and got results. However, the hourglass continues its endless > spiraling with the full dataset. > > I am running the following on Windows 7 > library(leaps) > m_250<-regsubsets(Y~., data=model2, nbest=1, really.big=TRUE) > > (NOTE: The ~ is a tilda, not a dash, in the regression statement above: Y~.) > > Does anyone have any opinions on: > 1) is R likely to still be running, even after a week, or should i just shut > it down?
It's likely to be running for years. 2^250 is a large number, even with the branch-and-bound algorithm to cut it down. > 2) am i doing something wrong with regsubsets? Yes. At the very least, set nvmax to something reasonable. You certainly don't want to find a model with 243 variables, so don't waste time looking for one. > > 3) is there a better option than regsubsets, Almost certainly. regsubsets() is pretty much useless as a way of selecting a single model, unless perhaps when p is very small. It was produced as a way of viewing a large collection of best models, as in the example for the plot() method, by setting nbest fairly large -thomas -- Thomas Lumley Professor of Biostatistics University of Auckland ______________________________________________ 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.
