[R] variable selectin---reduce the numbers of initial variable

[Ricardo Gonçalves Silva]

Hi,

Nowdays there's a lot o new variable selection methods, specially using the 
Bayes Paradigm.
For your problem, I think you could try the Bayesian Model Average BMA 
package.
Or, you can reduce your data dimension by PCA, which also permits you see 
the weight of
each variable in the PC.

HTH

Rick

--------------------------------------------------
From: "bbslover" <dluthm at yeah.net>
Sent: Wednesday, November 04, 2009 10:23 AM
To: <r-help at r-project.org>
Subject: [R]  variable selectin---reduce the numbers of initial variable

>
> hello,
>
> my problem is like this: now after processing the varibles, the remaining
> 160 varibles(independent) and a dependent y. when I used PLS method, with 
> 10
> components, the good r2 can be obtained. but I donot know how can I 
> express
> my equation with the less varibles and the y. It is better to use less
> indepent varibles.  that is how can I select my indepent varibles.   Maybe
> GA  is good method, but now I donot gasp it. and can you give me more good
> varibles selection's methods.   and In R, which method can be used to 
> select
> the potent varibles .  and using the selected varibles to model a equation
> with higher r2, q2,and less RMSP.
>
> thank you!
> -- 
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