[ADMB Users] help with glmmADMB 0.6.4 - function maximizer failed
bbolker at gmail.com
Fri Sep 23 08:44:37 PDT 2011
On 09/23/2011 10:39 AM, Rafael Mares wrote:
> Thank you very much for your replies.
> Ben, is a lognormal Poisson in lme4 the "same" as adding an
> observation level random effect to a Poisson model?
> If that's the
> case, I can run my model this way, with both random effects and all
> the data, no problem. The estimates seem reasonable to me.
Because neg binomial "type 2" (i.e. parameterized as V=mu*(1+mu/k))
has the same mean-variance relationship as the lognormal-Poisson (see
Elston et al 2001), I would generally expect the LNP and NB2 results to
be *reasonably* similar.
> The output from the glmmadmb model unfortunately doesn't mean much to
> me. But this is what it says right before the error:
> - final statistics:
> 9 variables; iteration 16; function evaluation 21
> Function value 8.0326e+03; maximum gradient component mag -2.7007e-05
> Exit code = 1; converg criter 1.0000e-04
> Var Value Gradient |Var Value Gradient |Var Value Gradient
> 1-26.04528 3.46314e-06 | 2-11.11848 -4.63363e-06 | 3 6.15104 1.90787e-06
> 4-18.30688 2.76734e-06 | 5-26.83680 4.50334e-06 | 6 5.36753 -1.32630e-05
> 7 5.04109 -2.67531e-06 | 8 6.48699 6.56383e-06 | 9 -0.09684 -2.70066e-05
> Hessian type 4
> inner maxg = 0.0009837 Inner second time = 0.0009837 Inner f = 7024
> f = 7024.448328266865 max g = 0.0009836751948745226
> Newton raphson 1 Error in glmmadmb
> The data seem ok to me, but I will try partitioning the data as you
> suggest to see if there are any particular data points causing
> problems. Thank you for your advice.
If I were you I would take Dave Fournier up on his offer, too.
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