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Bayesian Inference of State Space Models with the bssm Package

Helske, Jouni; Vihola, Matti

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.

Funded by Academy of Finland grant 284513, "Exact approximate Monte Carlo methods for complex Bayesian inference".
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