[R-sig-ME] glmm with correlated residuals

Joshua Wiley jwiley.psych at gmail.com
Fri Dec 21 09:00:16 CET 2012


No I was way off on this one (as in my previous reply to the OP).  I
was thinking general residual structures (not AR in particular) and I
missed the Poisson part so I thought SIR for spatial autocorrelation
could be generalized.



On Thu, Dec 20, 2012 at 12:53 PM, Ben Bolker <bbolker at gmail.com> wrote:
> Joshua Wiley <jwiley.psych at ...> writes:
>> Hi Emilio,
>> I would suggest doing it in MCMCglmm.  It can handle residual
>> structures too.  This is a nice starting guide:
>> http://cran.r-project.org/web/packages/MCMCglmm/vignettes/CourseNotes.pdf
>> Cheers,
>> Josh
>   Josh, are you sure?  I don't find "autoreg" anywhere in the course notes.
> I don't personally know of an easy way to do this other than using INLA
> (which I haven't tried much); glmmPQL (easy but perhaps dicey depending
> on the circumstances, and sometimes hard to figure out whether it's
> fitting a well-defined model); or hand-coding in WinBUGS/JAGS/Stan or
> AD Model Builder ...  You could also give up on Poisson-ness (you said
> there was heterogeneity of variance -- not quite sure what that means
> in this context?) and fit a GLS model with appropriate variance
> structure (using gls() with weights= and correlation= arguments set).
>   I'd love to hear other answers.
>   Ben
>> On Thu, Dec 20, 2012 at 8:37 AM, Emilio A. Laca <ealaca at ...> wrote:
>> > Fellow R users,
>> > what package would you recommend for fitting a poisson glmm with
>     one random effect and residuals that are correlated (most likely
>     AR(1)) and have heterogeneity of variance?  I have successfully
>     fitted the model without addressing the structured residuals in
>     MCMCglmm.  I would appreciate it very much if you could point me
>     in the direction of an example.
>> > Emilio A. Laca, Professor
>  [snip]
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Joshua Wiley
Ph.D. Student, Health Psychology
Programmer Analyst II, Statistical Consulting Group
University of California, Los Angeles

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