dear Alex,
I think your problem with a large number of predictors and a relatively
small number of subjects may be faced via some regularization approach
(ridge or lasso regression..)
hope this helps you,
vito
Alex Roy ha scritto:
Dear All,
I have a matrix say, X ( 100 X 40,000) and a vector say, y
(100 X 1) . I want to perform linear regression. I have scaled X matrix by
using scale () to get mean zero and s.d 1 . But still I get very high
values of regression coefficients. If I scale X matrix, then the regression
coefficients will bahave as a correlation coefficient and they should not be
more than 1. Am I right? I do not whats going wrong.
Thanks for your help.
Alex
*Code:*
UniBeta <- sapply(1:dim(X)[2], function(k)
+ summary(lm(y~X[,k]))$coefficients[2,1])
pval <- sapply(1:dim(X)[2], function(l)
+ summary(lm(y~X[,l]))$coefficients[2,4])
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--
====================================
Vito M.R. Muggeo
Dip.to Sc Statist e Matem `Vianelli'
Università di Palermo
viale delle Scienze, edificio 13
90128 Palermo - ITALY
tel: 091 6626240
fax: 091 485726/485612
http://dssm.unipa.it/vmuggeo
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