[R] covariate selection?

[Austin, Matt]

I like Kjetil's suggestion of a shrinkage estimator.  Perhaps this would be
a good time to experiment with Trevor Hastie's 'lars' package.

If you have a lot of correlated inputs I might suggest using Andy Liaw's
randomforest package.  I have found this technique to be very valuable in
this setting.  The partial dependency plots are a good way to explore the
functional relationships of the variables.

--Matt

-----Original Message-----
From: r-help-bounces at stat.math.ethz.ch
[mailto:r-help-bounces at stat.math.ethz.ch]On Behalf Of Kjetil Brinchmann
Halvorsen
Sent: Tuesday, October 12, 2004 17:16 PM
To: Ian Fiske
Cc: r-help at stat.math.ethz.ch
Subject: Re: [R] covariate selection?


Ian Fiske wrote:

> Hello,
>
> I am hoping someone can help me with the following multivariate 
> issue:  I have a model consisting of about 50 covariates.  I would 
> like to reduce this to about 5 covariate for the reduced model by 
> combining cofactors that are strongly correlated.  Is there a package 
> or function that would help me with this in R?  I appreciate any 
> suggestions.
>
> Thanks,
> Ian
>
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>
have a look at package leaps, and also consider ridge regression.

-- 

Kjetil Halvorsen.

Peace is the most effective weapon of mass construction.
               --  Mahdi Elmandjra

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