[R-sig-ME] hurdle model with glmmadmb

Ben Bolker bbolker at gmail.com
Thu Feb 9 14:58:45 CET 2012


Raquel Benavides <raquel.benavides at ...> writes:

> 
> I am afraid it isnt the problema, the bracket was missed during the copy
process in the mail...Any other idea?
> 
> -----Mensaje original-----
> De: Jarrod Hadfield [mailto:j.hadfield <at> ed.ac.uk] 
> 
> Hi,
> 
> missing bracket after parcela2?
> 
> Jarrod
> 
> Quoting Raquel Benavides <raquel.benavides <at> mncn.csic.es> on Thu, 9 Feb
> 2012 12:01:21 +0100:
> 
> > Dear all,
> >
> >
> >
> > I am trying to run glmmADMB to check the effect of some fixed effects 
> > over the number of seedlings in some plots (my random factors are 
> > site/transect/plot). In particular, I want to run a hurdle model. I 
> > have tried to follow the instructions given in athe document uploaded 
> > in the webpage http://glmmadmb.r-forge.r-project.org/. However I have 
> > some errors, and I don’t really understand what do they mean. Does 
> > anybody understand what it means and how to avoid it?
>
> > seed_hurdle1<-glmmadmb(seedling~I(Tanual^2)+(1|site/transecto/parcela2
> > ,data=
> > subset(datos,seedling>0),family="truncnbinom1")
> 
> > Error en glmmadmb(seedling ~ I(Tanual^2) + (1 | name/transecto/parcela),  :
> >
> >   The function maximizer failed (couldn't find STD file)
> >
> > Además: Mensajes de aviso perdidos
> >
> > 1: In glmmadmb(seedling ~ I(Tanual2^2) + (1 | name/transecto/parcela),  :
> >
> >   zero response values in truncated family
> >
> > 2: comando ejecutado 'C:\WINDOWS\system32\cmd.exe /c "C:/Archivos de 
> > programa/R/R-2.14.0/library/glmmADMB/bin/windows32/glmmadmb.exe" 
> > -maxfn 500 -maxph 5 -noinit -shess' tiene estatus 1

  Hmm.  It's surprising that you get the warning about zero response
values when you are explicitly using subset(datos, seedling>0).  Do you
by any chance have another copy of "seedling" lying around your
workspace, or have you attach()ed some data frames?  (This should
*not* break things, but it might anyway ...)

  You can try setting verbose=TRUE, although it will give you
loads of output where probably only the very end will be useful ...

  Are you willing to send me data?

  Ben Bolker




More information about the R-sig-mixed-models mailing list