[R-sig-ME] Negative Binomial in glmmadmb

Chad Newbolt newboch at auburn.edu
Thu Jun 30 17:40:44 CEST 2016

Based upon the responses I'm receiving it does not appear that some of my responses are being sent in the email chain.  I apologize if this duplicates a previously sent question...

I successfully loaded the glmmADMB package using the code below so thanks to Ben for that bit of help.

Since I have evidence for overdispersion, I'm using negative binomial distribution as opposed to Poisson.

My two questions are:

1) When I fit using the following global zero inflation model I receive the following error:

fit1=glmmadmb(Fawn~Age+I(Age^2)+BodySize+SSCM+AvgAge+Age*AvgAge+I(Age^2)*AvgAge+BodySize*AvgAge+SSCM*AvgAge+(1|Sire),data=datum,family="nbinom",zeroInflation = TRUE)
Parameters were estimated, but standard errors were not: the most likely problem is that the curvature at MLE was zero or negative
Error in glmmadmb(Fawn ~ Age + I(Age^2) + BodySize + SSCM + AvgAge + Age *  :
  The function maximizer failed (couldn't find parameter file) Troubleshooting steps include (1) run with 'save.dir' set and inspect output files; (2) change run parameters: see '?admbControl';(3) re-run with debug=TRUE for more information on failure mode
In addition: Warning message:
running command 'C:\windows\system32\cmd.exe /c glmmadmb -maxfn 500 -maxph 5 -noinit -shess' had status 1

However, when I change to zeroInflation = FALSE, I receive no warnings and everything seems to go as should.

Does this simply mean that my data is not zero inflated, hence the zero inflated model will not run, or is this something I should be concerned about and investigate the cause further?  When I debug   I see the following warning....Warning -- Hessian does not appear to be positive definite Hessian does not appear to be positive definite.

2) When fitting more simple versions(predictors removed) I receive the same error as above when using the family=nbinom;  however these errors disappear when using family=nbinom1.  Is this indicative of an underlying problem or am I OK to use the ouput from the later family where variance = ??.



	[[alternative HTML version deleted]]

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