[R-sig-ME] Need help on convergence issue when fitting zero-inflated Poisson with random coefficients using gamlss

[Ben Bolker]

    Since the proximal problem looks like (guessing from the error
messages) a call to the nlminb optimizer within a call to lme is
running out of iterations before converging, I'd try to see if there
is a way to set the number of parameters higher.  Unfortunately, I
don't know how to do this off the top of my head (a brief review of
the gamlss documentation didn't get me anywhere, and I haven't had
time to dig through the code to see if/how this is possible) ...

   There are other packages that are capable of fitting mixed ZIP
models (e.g. https://journal.r-project.org/archive/2017/RJ-2017-066/index.html
 shows examples using glmmTMB, inla, MCMCglmm, gamlss, ...) in case
you can't solve the problem with gamlss (and you aren't stuck using
gamlss for other reasons)

  cheers
   Ben Bolker


On Wed, Jan 22, 2020 at 2:01 PM Xia Li <odditylee using gmail.com> wrote:
>
> Hello,
>
> I have trouble getting convergence when fitting ZIP with (individual level)
> random coefficients, the function that I used:
>
> m1 <- gamlss(y ~ re(fixed = ~ treatment, random = ~ treatment|unit_id),
>              family = ZIP, data = dat)
>
> Specifically I wanted to include global or population level treatment
> effect, and individual random effect nested under treatment.
>
> I always got the following error messages:
>
> Error in lme.formula(fixed = fix.formula, data = Data, random = random, :
>    nlminb problem, convergence error code = 1
>    message = iteration limit reached without convergence (10)
>
> Is there anything that I can debug from? Changing the control parameters? I
> tried different algorithms like method = CG() but seems it did not help
> much.
>
> Looking for help. Thanks!
>
> --
> Best,
> Xia
>
>         [[alternative HTML version deleted]]
>
> _______________________________________________
> R-sig-mixed-models using r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-sig-mixed-models