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    Particle Metropolis–Hastings using gradient and Hessian information

    Particle Metropolis–Hastings (PMH) allows for Bayesian parameter inference in nonlinear state space models by combining Markov chain Monte Carlo (MCMC) and particle filtering. The latter is used to estimate th...

    Johan Dahlin, Fredrik Lindsten, Thomas B. Schön in Statistics and Computing (2015)