Tag Archives: sequential Monte Carlo

Why and how pseudo-marginal MCMC work for exact Bayesian inference

I will describe a breakthrough strategy for “exact-approximate” Bayesian inference. The apparent contradiction in the terminology is due to the surprising result in Beaumont (2003) and Andrieu and Roberts (2009) where it is shown that plugging a non-negative and unbiased … Continue reading

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Sequential Monte Carlo and the bootstrap filter

In the previous post I have outlined three possibilities for approximating the likelihood function of a state space model (SSM). That post is a required read to follow the topics treated here. I concluded with sequential importance sampling (SIS), which … Continue reading

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