[R] logistic regression based on principle component analysis
Kjetil Halvorsen
kjetilbrinchmannhalvorsen at gmail.com
Thu Jan 7 18:27:02 CET 2010
for an alternative (lasso) approach, look at the packages (CRAN)
grpreg, grplasso, glmnet, penalized and certainly some others.
Kjetil B H
On Thu, Jan 7, 2010 at 2:06 PM, Steve Lianoglou
<mailinglist.honeypot at gmail.com> wrote:
> Hi,
>
> On Thu, Jan 7, 2010 at 11:57 AM, 江文恺 <biology0046 at hotmail.com> wrote:
>>
>> Dear all:
>>
>> I try to analyse a dataset which contain one binary response variable and serveral predict variables, but multiple colinear problem exists in my dataset, some paper suggest that logistic regression for principle components is suit for these noise data,
>> but i only find R can done principle component regression using "pls" package,
>> is there any package that can do the task i need - logistic regression based on principle components,
>> if not, can anyone give some suggestion about how to use R to do my work.
>
> Is this any different than first doing PCA to do the dimensionality
> reduction (which presumably will take care of your colinearity), then
> doing the logistic regression on your reduced input space?
>
> If so: no package is really necessary, right? It's just a two-step
> solution you need to write up.
>
> -steve
> --
> Steve Lianoglou
> Graduate Student: Computational Systems Biology
> | Memorial Sloan-Kettering Cancer Center
> | Weill Medical College of Cornell University
> Contact Info: http://cbio.mskcc.org/~lianos/contact
>
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