Is there an R-Package I could use for Bayesian parameter estimation as an alternative to JAGS? I found an old question regarding JAGS/BUGS alternatives in R, however, the last post is already 9 years old. So maybe there are new and flexible gibbs sampling packages available in R? I want to use it to get parameter estimates for novel hierarchical hidden markov models with random effects and covariates etc. I highly value the flexibility of JAGS and think that JAGS is simply great, however, I want to write R functions that facilitate model specification and am looking for a package that I can use for parameter estimation.
There are some alternatives:
stan, with rstan R package. Stan looks well optimized but cannot do certain type of models (like binomial/poisson mixture model), since he cannot sample a discrete variable (or something like that...).
nimble
if you want highly optimized sampling based on C++, you may want to check Rcpp based solutions from Dirk Eddelbuettel