subset selection for logistic regression

-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch 
[mailto:r-help-bounces at stat.math.ethz.ch] On Behalf Of Wittner, Ben
Sent: 02 March 2005 11:33
To: r-help at lists.R-project.org
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."

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