Could you advise if cor_arma is now available for a negative binomial or Poisson model? I try this function for my model and it produces strange results:
fit1=brm(count ~ scale(sqrt(ba.p))*scale(log(bai_cm2_year.p))+ scale(log(ccf.p))*scale(log(height_m.p))+species.p+(1|location_id/id.m), data=dat2, family=negbinomial(“log”), autocor = cor_arma(~1|year:id.m, 1, 1, cov = TRUE), prior=bprior1, cores = 4, iter = 1000 + 7000, warmup = 1000, chains = 3, seed=123),
where year is a factor.
The model converges without problem but posterior means for species are completely off the observed data. In turn, without cor_arma, the model shows good fit but up to 5 lags high autocorrelation for some variables. You mentioned previously, cor_arma was developed only for Gaussian family - https://github.com/paul-buerkner/brms/issues/320, is it now available also for a negative binomial model?
- Operating System: Windows10
- brms Version: 2.13.3
Thank you in advance for your hints!