[R] lme, corARMA and large data sets

[Dimitris Rizopoulos]

you should include the 'form' argument in "corARMA()", i.e.,

corARMA(form=~1|dummy, p=1, q=1)


I hope it helps.

Best,
Dimitris

----
Dimitris Rizopoulos
Ph.D. Student
Biostatistical Centre
School of Public Health
Catholic University of Leuven

Address: Kapucijnenvoer 35, Leuven, Belgium
Tel: +32/16/336899
Fax: +32/16/337015
Web: http://www.med.kuleuven.ac.be/biostat/
     http://www.student.kuleuven.ac.be/~m0390867/dimitris.htm


----- Original Message ----- 
From: "Peter Wandeler" <p_wandeler at gmx.ch>
To: <R-help at stat.math.ethz.ch>
Sent: Thursday, April 14, 2005 2:12 PM
Subject: [R] lme, corARMA and large data sets


>I am currently trying to get a "lme" analyses running to correct for 
>the
> non-independence of residuals (using e.g. corAR1, corARMA) for a 
> larger data
> set (>10000 obs) for an independent (lgeodisE) and dependent 
> variable
> (gendis). Previous attempts using SAS failed. In addition we were 
> told by
> SAS that our data set was too large to be handled by this procedure 
> anyway
> (!!).
>
> SAS script
> proc mixed data=raw method=reml maxiter=1000;
> model gendis=lgeodisE / solution;
> repeated /subject=intercept type=arma(1,1);
>
> So I turned to R. Being a complete R newbie I didn't arrive 
> computing
> exactly the same model in R on a reduced data set so far.
>
> R command line (using "dummy" as a dummy group variable)
>>
> model.ARMA<-lme(gendis~lgeodisE,correlation=corARMA(p=1,q=1),random=~1|dummy).
>
> Furthermore, memory allocation problems occurred again on my 1GB RAM 
> desktop
> during some trials with larger data sets.
>
> Can anybody help?
> Cheers,
> Peter
>
> -- 
>
>
> GMX Garantie: Surfen ohne Tempo-Limit! http://www.gmx.net/de/go/dsl
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