Hello Ian,
Sorry. I don't really understand your problem, which is of model selection. That's
right?
You could use some criteria based in likelihood. For instante Akaike (AIC) or Schwarz
criteria (BIC), see:
?AIC
?mle.aic
(The best model is determined minimizing AIC or BIC).
I hope this help you.
Greetings,
Juan Carlos
-----Mensaje original-----
De: Ian Fiske [mailto:[EMAIL PROTECTED]
Enviado el: Martes, 12 de Octubre de 2004 05:17 PM
Para: Mart�nez Ovando Juan Carlos
CC: [EMAIL PROTECTED]
Asunto: Re: [R] covariate selection?
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
Mart�nez 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 Mart�nez Ovando
>Banco de M�xico
>Av. 5 de Mayo No. 18
>Piso 5 Secci�n D
>Col. Centro
>06059 M�xico, D. F.
>Tel. +52 55 52.37.20.00 ext. 3594
>Fax. +52 55 52.37.27.03
>e-mail: [EMAIL PROTECTED]
>
>
>-----Mensaje original-----
>De: Ian Fiske [mailto:[EMAIL PROTECTED]
>Enviado el: Martes, 12 de Octubre de 2004 04:08 PM
>Para: [EMAIL PROTECTED]
>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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