logistic regression based on principle component analysis

From: Kjetil Halvorsen <kjetilbrinchmannhalvorsen at gmail.com>
Subject: Re: [R] logistic regression based on principle component analysis
To: "Steve Lianoglou" <mailinglist.honeypot at gmail.com>
Cc: r-help at r-project.org, "???" <biology0046 at hotmail.com>
Date: Thursday, January 7, 2010, 12:27 PM
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, ??? <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

mailing list

reproducible code.