[R] covariate selection?

[Ian Fiske]

Thanks Juan.  I thought that was what I was looking for, but really, I 
want to know which of the original covariates could best be used to take 
advantage of their colinearity without creating new variables.  I think 
PCA creates new variables.  SAS and SPSS can do what I'm talking about, 
but I would like to use R for this.

Thanks,
Ian



Martínez Ovando Juan Carlos wrote:

>Hello Ian,
>
>?princomp
>
>If your covariates are scalars, and the following documents:
>
>http://www.jstatsoft.org/v07/i01/drdoc.pdf
>
>http://www.bioconductor.org/workshops/Milan/PDF/Lab12.pdf
>
>
>Best wishes. 
>
>Saludos,
> 
>Juan Carlos Martínez Ovando
>Banco de México
>Av. 5 de Mayo No. 18
>Piso 5 Sección D
>Col. Centro
>06059  México, D. F.
>Tel. +52 55 52.37.20.00 ext. 3594
>Fax. +52 55 52.37.27.03
>e-mail: jcmartinez at banxico.org.mx
> 
>
>-----Mensaje original-----
>De: Ian Fiske [mailto:ifiske at ufl.edu] 
>Enviado el: Martes, 12 de Octubre de 2004 04:08 PM
>Para: r-help at stat.math.ethz.ch
>Asunto: [R] covariate selection?
>
>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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