Abstract
This chapter gives an introduction to sequential simulation methods, a collection of algorithms that build both on MCMC methods and importance sampling, with importance sampling playing a key role. We will see the relevance of importance sampling and the limitations of standard MCMC methods in many settings, as we try to make the reader aware of important and ongoing developments in this area. In particular, we present an introduction. to Population Monte Carlo (Section 14.4), which extends these notions to a more general case, and subsumes MCMC methods
“The past is important, sir,” said Rebus, taking his leave.
—Ian Rankin, The Black Book
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Robert, C.P., Casella, G. (2004). Iterated and Sequential Importance Sampling. In: Monte Carlo Statistical Methods. Springer Texts in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4757-4145-2_14
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DOI: https://doi.org/10.1007/978-1-4757-4145-2_14
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