HI Ben,

Many thanks for clarifying this.

Julia

2013/5/21 Ben Bolker <bbolker@gmail.com>

> On 13-05-20 06:19 AM, Julia Sommerfeld wrote:
> > Dear list,
> >
> > I'm trying to fit a glmmadmb, but I'm always getting the following error
> > message:
> >
> > *mod <- glmmadmb(anzahl_round~wea1*seg + offset(log(flaeche)) +
> > (1|day_ID) + (1|seg), zeroInflation=TRUE, family="poisson", data=dat1)  *
> >
> > /Parameters were estimated, but not standard errors were not: the most
> > likely problem is that the curvature at MLE was zero or negative
> > Error in glmmadmb(anzahl_round ~ wea1 * seg + offset(log(flaeche)) + (1
> > |  :
> >   The function maximizer failed (couldn't find STD file) Troubleshooting
> > steps include (1) run with 'save.dir' set and inspect output files; (2)
> > change run parameters: see '?admbControl'
> > In addition: Warning message:
> > running command 'C:\Windows\system32\cmd.exe /c
> >
> "C:/Users/Hawksbill/Documents/R/win-library/3.0/glmmADMB/bin/windows32/glmmadmb.exe"
> > -maxfn 500 -maxph 5 -noinit -shess' had status 1 /
> >
>
>   Update:
>
> I can replicate this problem, and we are working on a tweak that will
> allow glmmADMB to fit this model.  However, in the meantime I have some
> advice ...
>
>  This case is similar to the previous one posted here.  The essential
> problem is that the data are highly overdispersed (with or without
> zero-inflation), so that estimates of the predicted Poisson mean
> underflow to zero, which throws off the estimation.  In the absence of
> being able to fit the ZIP, you can confirm pretty well that the ZINB is
> a better model by looking at the summary of the ZINB and seeing that the
> estimated alpha (overdispersion parameter) is small, with a small
> standard error -- therefore NB will be better than Poisson.
>
>   A couple of other points to note, though:
>
> * you should not be trying to fit seg as both a fixed and a random
> factor. By putting wea1*seg in the formula, you are implicitly including
> the main effects of wea1 and seg and their interaction (the interaction
> alone would be written wea1:seg.  You might want ~wea1+wea1:seg ?
>
> * the results of fitting ZINB and NB are a little weird, possibly for
> this reason (the NB fits better [has a lower negative log-likelihood]
> than the ZINB, which should be impossible)
>
> * you might also want to check the mean-variance scaling/consider
> family="nbinom1"
>
> * in all the models I fitted (ZIP, P, ZINB, NB) the 1|seg variance comes
> out as zero, again probably because of the redundancy described above.
> Even when you don't have redundancy in your model this sort of thing
> happens sometimes, indicating that your random-effects model is slightly
> overfitted.
>
>
>

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