Particle Metropolis-Hastings using gradient and Hessian information

4 Nov 2013Johan DahlinFredrik LindstenThomas B. Schön

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 the intractable likelihood... (read more)

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