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])
>
> [[alternative HTML version deleted]]
>
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--
===================================Vito M.R. Muggeo
Dip.to Sc Statist e Matem `Vianelli'
Universit? di Palermo
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90128 Palermo - ITALY
tel: 091 6626240
fax: 091 485726/485612
http://dssm.unipa.it/vmuggeo