Uniform Stability of a Particle Approximation of the Optimal Filter Derivative

DOI10.1137/140993703zbMath1349.65010arXiv1106.2525OpenAlexW2963478176MaRDI QIDQ5254903

Pierre Del Moral, Sumeetpal S. Singh, Arnaud Doucet

Publication date: 10 June 2015

Published in: SIAM Journal on Control and Optimization (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1106.2525

zbMATH Keywords

smoothingcentral limit theoremhidden Markov modelsstate-space modelsparticle approximation\(\mathbb{L}_{p}\) boundsfilter derivativesequential Monte Carlo mehods

Mathematics Subject Classification ID

Filtering in stochastic control theory (93E11) Markov processes: estimation; hidden Markov models (62M05) Monte Carlo methods (65C05) Discrete-time Markov processes on general state spaces (60J05) Identification in stochastic control theory (93E12) Stochastic particle methods (65C35)

Related Items (8)

Bandwidth selection in pre-smoothed particle filters ⋮ Stability of optimal filter higher-order derivatives ⋮ Backward Importance Sampling for Online Estimation of State Space Models ⋮ Nested particle filters for online parameter estimation in discrete-time state-space Markov models ⋮ Gradient free parameter estimation for hidden Markov models with intractable likelihoods ⋮ Particle-based online estimation of tangent filters with application to parameter estimation in nonlinear state-space models ⋮ Bias of Particle Approximations to Optimal Filter Derivative ⋮ On particle methods for parameter estimation in state-space models

Cites Work

• Particle approximations of the score and observed information matrix in state space models with application to parameter estimation
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• Asymptotic Statistics
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