Please use this identifier to cite or link to this item: https://doi.org/10.1214/13-AOS1172
Title: A general theory of particle filters in hidden markov models and some applications
Authors: Chan, H.P. 
Lai, T.L.
Keywords: Importance sampling and resampling
Particle filter
Standard error
Issue Date: Dec-2013
Citation: Chan, H.P., Lai, T.L. (2013-12). A general theory of particle filters in hidden markov models and some applications. Annals of Statistics 41 (6) : 2877-2904. ScholarBank@NUS Repository. https://doi.org/10.1214/13-AOS1172
Abstract: By making use of martingale representations, we derive the asymptotic normality of particle filters in hidden Markov models and a relatively simple formula for their asymptotic variances. Although repeated resamplings result in complicated dependence among the sample paths, the asymptotic variance formula and martingale representations lead to consistent estimates of the standard errors of the particle filter estimates of the hidden states. © Institute of Mathematical Statistics, 2013.
Source Title: Annals of Statistics
URI: http://scholarbank.nus.edu.sg/handle/10635/104930
ISSN: 00905364
DOI: 10.1214/13-AOS1172
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