Sequential Monte Carlo as approximate sampling: bounds, adaptive resampling via \(\infty\)-ESS, and an application to particle Gibbs

DOI10.3150/17-BEJ999MaRDI QIDQ1715543

Jonathan H. Huggins, Daniel M. Roy

Publication date: 28 January 2019

Published in: Bernoulli (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1503.00966

zbMATH Keywords

state-space modelssequential Monte Carlogeometric ergodicityuniform ergodicityeffective sample sizeparticle Gibbsadaptive resampling

Mathematics Subject Classification ID

Computational methods in Markov chains (60J22) Bayesian inference (62F15) Monte Carlo methods (65C05) Interacting random processes; statistical mechanics type models; percolation theory (60K35) Numerical analysis or methods applied to Markov chains (65C40)

Related Items (1)

An Invitation to Sequential Monte Carlo Samplers

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