[R-sig-ME] increasing maximum iterations in glmmadmb function
bbolker at gmail.com
Thu Jan 28 00:11:19 CET 2016
[Please keep r-sig-mixed-models in the Cc: list ...]
Nothing stands out particularly strongly from this summary; the one
guess would be, since you have rather large parameter estimates
(abs(beta)>5) in a binomial-response model, that you are encountering
a problem of complete separation (i.e., that some combinations of
predictor variables have all- (or nearly-all)-negative or all-positive
responses, leading to infinite parameter estimates under MLE).
However, in my experience usually such cases give even larger
parameter estimates (e.g. abs(beta)>8).
Since this particular model is fairly standard (binomial GLMM,
standard logit link, no zero-inflation) it should be fairly easy to
run it with another platform/package (MASS::glmmPQL, lme4::glmer,
glmmML, MCMCglmm ...) and see if you get similar answers.
On Wed, Jan 27, 2016 at 3:11 PM, Reuben Smit <smit.reuben at gmail.com> wrote:
> Thanks for the help query, that is what I was looking for.
> The warning does not include anything but "Convergence failed: log
> likelihood -0.1037". You were right about increasing the iterations not
> helping, though.
> The following is the model summary, if you notice anything immediately,
> please let me know, otherwise I will continue with model diagnostics, etc.
> This model is a set of models for model based hypotheses. Thanks again for
> any help you can offer.
> glmmadmb(formula = A_Neis_PA ~ HMU + Dist2bank + DistAC + Sinu +
> (1 | Site_fact), data = mussel, family = "binomial")
> Estimate Std. Error z value Pr(>|z|)
> (Intercept) 6.3850 2.0309 3.14 0.00167 **
> HMUB1 2.6482 0.7720 3.43 0.00060 ***
> HMUB2 2.9078 0.8030 3.62 0.00029 ***
> HMUC -0.4973 1.2842 -0.39 0.69856
> HMUD 4.2994 1.0260 4.19 2.8e-05 ***
> Dist2bank -0.1279 0.0337 -3.79 0.00015 ***
> DistAC 0.0165 0.0418 0.40 0.69220
> Sinu -5.7189 1.6773 -3.41 0.00065 ***
> Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
> Number of observations: total=259, Site_fact=20
> Random effect variance(s):
> Variance StdDev
> (Intercept) 0.2957 0.5438
> On Wed, Jan 27, 2016 at 10:53 AM, Ben Bolker <bbolker at gmail.com> wrote:
>> Did you look at ?admbControl ?
>> "failing to converge" is a pretty broad category; if for example the
>> warning message says something about a non-positive-definite Hessian at the
>> optimum, increasing the number of iterations may not help that much ...
>> On 16-01-27 12:53 PM, Reuben Smit wrote:
>>> My binomial mixed model is failing to converge, so I would like to
>>> the number of iterations. However, upon research I cannot find
>>> solutions for glmmadmb function specifically. I must be missing
>>> something. Any guidance would be appreciated.
>> R-sig-mixed-models at r-project.org mailing list
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