Limit theorems for sequential MCMC methods

Both sequential Monte Carlo (SMC) methods (a.k.a. ‘particle filters’) and sequential Markov chain Monte Carlo (sequential MCMC) methods constitute classes of algorithms which can be used to approximate expectations with respect to (a sequence of) probability distributions and their normalising const...

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Bibliographic Details

Main Authors:	Axel Finke, Arnaud Doucet, Adam M Johansen
Format:	Default Article
Published:	2020
Subjects:	Statistics not elsewhere classified Sequential Monte Carlo methods Particle filters Markov chain Monte Carlo methods Almost sure convergence Multivariate central limit theorem Time-uniform convergence Statistics
Online Access:	https://hdl.handle.net/2134/12845810.v1
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