R help - Jul 2004 - Performance problem

Dear all,
I have a performance problem in terms of computing time.
I estimate mixed models on a fairly large number of subgroups (10000) using
lme(.) within the by(.) function and it takes hours to do the calculation
on a fast notebook under Windows.
I suspect by(.) to be a poor implementation for doing individual analysis
on subgroups.
Is there an alternative and more efficient way for doing by-group
processing within lme(.).

Here some code to give you a glimpse
gfit <- by(longdata, gen, function(x) lme(fixed=response ~ dye + C(treat,
base = 4 ),
            data=x,random =~ 1 | slide)  )

Thanks in advance & regards
Gerhard Krennrich


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Gerhard Krennrich
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>Date: Tue, 20 Jul 2004 11:23:25 +0200
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>Subject: [R] Performance problem
>Message: 60
>
>Dear all,
>I have a performance problem in terms of computing time.
>I estimate mixed models on a fairly large number of subgroups (10000) using
>lme(.) within the by(.) function and it takes hours to do the calculation
>on a fast notebook under Windows.
>I suspect by(.) to be a poor implementation for doing individual analysis
>on subgroups.
>Is there an alternative and more efficient way for doing by-group
>processing within lme(.).
>
>Here some code to give you a glimpse
>gfit <- by(longdata, gen, function(x) lme(fixed=response ~ dye + C(treat,
>base = 4 ),
>            data=x,random =~ 1 | slide)  )
>
>Thanks in advance & regards
>Gerhard Krennrich
>
Sorry, that I can't contribute to a solution. But I have a similar problem,
doing lme's on 350 source estimations of MEG brain data. So if somebody
knows some improvement, please let me know !

Stephan Moratti



-----------------------------
Dipl. Psych. Stephan Moratti
Dept. of Psychology
University of Konstanz
P.O Box D25
Phone: +40 (0)7531 882385
Fax: +49 (0)7531 884601
D-78457 Konstanz, Germany

e-mail: Stephan.Moratti at uni-konstanz.de
http://www.clinical-psychology.uni-konstanz.de/