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

[bbslover]

thank you . I can try bayesian. PCA method that I used to is can get some
pcs, but I donot know how can i use the original variables in that equation,
maybe I should select those have high weight ones,and delete that less
weight ones. right?

Ricardo Gonçalves Silva wrote:
> 
> 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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> 
> 
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