Sequential Monte Carlo samplers: error bounds and insensitivity to initial conditions

Research output: Contribution to journalArticle (Academic Journal)peer-review

15 Citations (Scopus)

Abstract

This article addresses finite sample stability properties of sequential Monte Carlo methods for approximating sequences of probability distributions. The results presented herein are applicable in the scenario where the start and end distributions in the sequence are fixed and the number of intermediate steps is a parameter of the algorithm. Under assumptions which hold on noncompact spaces, it is shown that the effect of the initial distribution decays exponentially fast in the number of intermediate steps and the corresponding stochastic error is stable in p norm.
Original languageEnglish
Pages (from-to)774-798
Number of pages25
JournalStochastic Analysis and Applications
Volume30
Issue number5
Early online date10 Aug 2012
DOIs
Publication statusPublished - Sep 2012

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