At 09:35 AM 14/07/2005, Emilio A. Laca wrote: >I need to specify a model similar to this > >lme.formula(fixed = sqrt(lbPerAc) ~ y + season + y:season, data = cy, > random = ~y | observer/set, correlation = corARMA(q = 6)) > >except that observer and set are actually crossed instead of nested.
Does this work for you? (following P&B pp 162-3 and an R-help archive search on "crossed random effects")... fit <- lme(sqrt(lbPerAc) ~ y * season, random=list(pdBlocked(pdIdent(~y), pdIdent(observer-1), pdIdent(set-1))), correlation=corARMA(q = 6), data=cy) lme isn't very well set up for crossed random effects. It's easier in lmer. I don't think lmer can handle alternative correlation structures yet, though. (Prof. Bates?) HTH, Simon. >observer and set are factors >y and lbPerAc are numeric > >If you know how to do it or have suggestions for reading I will be >grateful. > > >eal > >ps I have already read Pinheiro & Bates, the jan 05 newsletter, and >several postings. > >______________________________________________ >R-help@stat.math.ethz.ch mailing list >https://stat.ethz.ch/mailman/listinfo/r-help >PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Simon Blomberg, B.Sc.(Hons.), Ph.D, M.App.Stat. Centre for Resource and Environmental Studies The Australian National University Canberra ACT 0200 Australia T: +61 2 6125 7800 email: Simon.Blomberg_at_anu.edu.au F: +61 2 6125 0757 CRICOS Provider # 00120C ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html