I’m quite new to Stan. I used to use JAGS all the time though. I have a question about how to do dynamic models on count data in a panel setting. I’m trying to run fixed effect dynamic models on panel event count data and see the instantaneous and long-run effects of the covariates after taking into the AR coefficient. However, I don’t know how to write the model in Stan, as it’s different from a linear case when you have a lagged dependent variable as counts due to non-linear feedback. See below for discussion in the frequentist realm. http://fmwww.bc.edu/repec/msug2010/mex10sug_trivedi.pdf
I’ve seen a post in the forum about dynamic panel models (Dynamic panel data models with Stan?), but it doesn’t discuss the situation when the dependent variable is of other types of distribution, such as Poisson, binomial etc. In the linear case, after estimating the model, we can get AR(1) coefficient for calculating the long-run effect of any betas of interest. But in a poisson case, the AR coefficient can no longer be used in that way. Does anyone have experience with this kind of models? I would be super grateful if someone can help me with doing dynamic panel model for count data in Stan.
Many thanks in advance!