Bayesian Inference of State Space Models with the bssm Package

Efficient methods for Bayesian inference of state space models via particle Markov chain Monte Carlo and importance sampling type corrected Markov chain Monte Carlo. Currently supports models with Gaussian, Poisson, binomial, or negative binomial observation densities and Gaussian state dynamics, as well as general non-linear Gaussian models.