Negative Binomial in glmmadmb
Exactly as you would do it in glmmADMB, just replace ADMB with TMB... Check the github examples: https://github.com/glmmTMB/glmmTMB/tree/master/glmmTMB/tests/testthat
On 01.07.2016 21:47, Chad Newbolt wrote:
Thanks so much for the response. I know this is probably very simple but how do I denote the family as negative binomial using glmmTMB? I've dug through text regarding this package and have had trouble coming up with anything that works. Chad
________________________________________
From: R-sig-mixed-models <r-sig-mixed-models-bounces at r-project.org> on behalf of Ben Bolker <bbolker at gmail.com>
Sent: Thursday, June 30, 2016 7:45 PM
To: r-sig-mixed-models at r-project.org
Subject: Re: [R-sig-ME] Negative Binomial in glmmadmb
Chad Newbolt <newboch at ...> writes:
[snip]
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)
I think you can shorten this a bit to
(Age+I(Age^2)+BodySize+SSCM)*AvgAge + (1|Sire)
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 = ??. Thanks, Chad [[alternative HTML version
deleted]]
Short answer: you should be a little concerned, and you should
not assume that your data are not zero-inflated. These are not
indications about what your model is actually finding, just indications
that ADMB ran into *some* kind of trouble. Unfortunately,
there is no really simple guide to trouble-shooting these kinds of
problems. Some general suggestions:
* try out the glmmTMB package - it's newer/experimental, but
often more stable
* the ?admbControl man page suggests trying shess=FALSE and noinit=FALSE
* it may not help in this case, but centering continuous predictors is
always worth a shot
* similarly, poly(Age,2) is a little more stable than (Age+I(Age^2))
* inspect your data graphically to see whether there are outliers
or other odd patterns that might be messing up the fit
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