bbolker wrote: > > emmarosenfeld <emmarosenfeld <at> hotmail.co.uk> writes: > >> >> Dear all, >> >> I am having some problems trying to run a GLMM model with zero-inflation >> using the alpha version of glmmADMB (0.6.4) using R (2.13.1) in Windows >> and >> I would greatly appreciate some help. >> My count response variable (number of birds: count) fits a negative >> binomial >> distribution and the explanatory variables are both continuous and >> categorical (species= 17). The three random effects are site (68 of >> them), >> season (1 or 2) and land class (1 to 6). > > You mean species is a factor with 17 levels? > > I am trying to analyse the count data of 17 different species in the same > model as it's a community based analysis. > > What are the results of str(srp12) ? > > Results= > 'data.frame': 2312 obs. of 12 variables: > $ site : Factor w/ 68 levels "site1","site10",..: 1 12 23 33 54 65 67 > 68 2 3 ... > $ season : Factor w/ 2 levels "season1","season2": 1 1 1 1 1 1 1 1 1 1 > ... > $ count : int 23 9 6 14 12 6 10 4 9 7 ... > $ species : Factor w/ 17 levels "B","BF","BT",..: 1 1 1 1 1 1 1 1 1 1 > ... > $ site.1 : Factor w/ 68 levels "site1","site10",..: 1 12 23 33 54 65 67 > 68 2 3 ... > $ built : num 0.274 0.297 0.326 0.27 0.337 ... > $ atrees : num 0.0482 0.0498 0.0443 0.0822 0.0523 ... > $ btrees : num 0.81 0.847 0.884 0.88 0.851 ... > $ Ctrees : num 16.8 17 19.9 10.7 16.3 ... > $ landclass: Factor w/ 6 levels "land1","land2",..: 3 3 3 3 3 3 3 3 3 3 > ... > $ distance : Factor w/ 1 level "dist0500": 1 1 1 1 1 1 1 1 1 1 ... > $ distcont : int 500 500 500 500 500 500 500 500 500 500 ... > > > You are going to have a lot of difficulty fitting a random effect > to a factor with two levels (see http://glmm.wikidot.com/faq for > discussion). Try it as a fixed effect instead. > > Are you referring to season as a factor with two levels? I'll try it as > fixed instead. > >> Ideally I would also like to build >> in a variance structure to allow a different spread per land class. > > I don't know of a way to do this in glmmADMB. **Maybe** doable > in MCMCglmm but I wouldn't count on it. > >> This is >> the model I'm trying to run: >> (fm<-glmmadmb(count~species*btrees+species*built+species*btrees*built+ > (1|season)+(1|landclass)+(1|site), > data=srp12, famil="nbinom", zeroInflation=TRUE)) > > Are you aware that species*btrees*built expands to include > all main effects, two- and three-way interactions, i.e. the > species*btrees and species*built terms are redundant. > > I hadn't realised that species*btrees*built allows for both two- and > three- way interactions, no, i thought I had to specify those. Thanks for > that. > >> I have read most of the supporting documents to glmmADMB and studied the >> examples but am still struggling to make headway. >> >> This is the error message I get; >> >> Memory allocation error -- Perhaps you are trying to allocate too much >> memory in your program >> Warning: running command 'C:\Windows\system32\cmd.exe /c >> "C:/R-2.13.1/library/glmmADMB/bin/windows32/glmmadmb.exe" -maxfn 500' had >> status 1 >> Warning in shell(cmd, invisible = TRUE) : >> '"C:/R-2.13.1/library/glmmADMB/bin/windows32/glmmadmb.exe" -maxfn 500' >> execution failed with error code 1 >> Error in glmmadmb(count ~ species * btrees + species * built + species * >> : >> The function maximizer failed > > >> >> I have also run: >> >> > summary(fm) >> >> Which results in: >> >> Error in summary(fm) : object 'fm' not found > > Well, that's not surprising since the command failed. >> >> This has happened however the equation is labelled. >> >> Perhaps there is a more appropriate package that I should be using >> (MCMCglmm)? >> I am quite new to R, so it is quite possible that I am missing something, >> so >> any help would be most appreciated. >> > > ______________________________________________ > R-help@ mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. >
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