Robin,

You may see leaps() (package leaps). It deals with all subsets regression considering several chosen criteria.

beste Regards,
Alex



 models ---------- Início da mensagem original -----------
De: r-help-bounces@stat.math.ethz.ch
Para: "Smit, Robin" robin.smit@tno.nl
Cc: r-help@stat.math.ethz.ch
Data: Thu, 24 Feb 2005 07:15:03 -0500
Assunto: Re: [R] Forward Stepwise regression based on partial F test
> Smit, Robin wrote:
> > I am hoping to get some advise on the following:
> >
> > I am looking for an automatic variable selection procedure to reduce the
> > number of potential predictor variables (~ 50) in a multiple regression
> > model.
> >
> > I would be interested to use the forward stepwise regression using the
> > partial F test.
> > I have looked into possible R-functions but could not find this
> > particular approach.
> >
> > There is a function (stepAIC) that uses the Akaike criterion or Mallow's
> > Cp criterion.
> > In addition, the drop1 and add1 functions came closest to what I want
> > but with them I cannot perform the required procedure.
> > Do you have any ideas?
> >
> > Kind regards,
> > Robin Smit
> > --------------------------------------------
> > Business Unit TNO Automotive
> > Environmental Studies & Testing
> > PO Box 6033, 2600 JA Delft
> > THE NETHERLANDS
>
> Robin,
>
> If you are looking for a method that does not offer the best predictive
> accuracy and that violates every aspect of statistical inference, you
> are on the right track. See
> http://www.stata.com/support/faqs/stat/stepwise.html for details.
>
> --
> Frank E Harrell Jr Professor and Chair School of Medicine
> Department of Biostatistics Vanderbilt University
>
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