Long-term stability of sequential Monte Carlo methods under verifiable conditions

DOI10.1214/13-AAP962zbMath1429.62364arXiv1203.6898OpenAlexW3101877509MaRDI QIDQ744372

Jimmy Olsson, Eric Moulines, Randal Douc

Publication date: 25 September 2014

Published in: The Annals of Applied Probability (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1203.6898

zbMATH Keywords

asymptotic variancesequential Monte Carlo methodsgeneral hidden Markov modelsbootstrap particle filterlocal Doeblin conditiontime uniform convergence

Mathematics Subject Classification ID

Asymptotic properties of parametric estimators (62F12) Inference from stochastic processes and prediction (62M20) Markov processes: estimation; hidden Markov models (62M05) Signal detection and filtering (aspects of stochastic processes) (60G35)

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Fluctuations, stability and instability of a distributed particle filter with local exchange, On the convergence of adaptive sequential Monte Carlo methods, Piecewise deterministic Markov processes for continuous-time Monte Carlo, A sharp first order analysis of Feynman-Kac particle models. I: Propagation of chaos, On the Behaviour of the Backward Interpretation of Feynman-Kac Formulae Under Verifiable Conditions, On the mathematical theory of ensemble (linear-Gaussian) Kalman-Bucy filtering, On the stability of positive semigroups, Twisted particle filters, Numerically stable online estimation of variance in particle filters, Stability with respect to initial conditions in V-norm for nonlinear filters with ergodic observations, Path storage in the particle filter, Particle-based online estimation of tangent filters with application to parameter estimation in nonlinear state-space models, Error estimates on ergodic properties of discretized Feynman-Kac semigroups, Limit theorems for sequential MCMC methods

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