Whiteley, Nick, Johansen, Adam M. and Godsill, Simon J., 1965-. (2011) Monte Carlo filtering of piecewise deterministic processes. Journal of Computational and Graphical Statistics, Vol.20 (No.1). pp. 119-139. ISSN 1537-2715

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Abstract

We present efficient Monte Carlo algorithms for performing Bayesian inference in a broad class of models: those in which the distributions of interest may be represented by time marginals of continuous-time jump processes conditional on a realisation of some noisy observation sequence. The sequential nature of the proposed algorithm makes it particularly suitable for online estimation in time series. We demonstrate that two existing schemes can be interpreted as particular cases of the proposed method. Results are provided which illustrate significant performance improvements relative to existing methods. The appendix to this document can be found online.

Item Type:	Journal Article
Subjects:	Q Science > QA Mathematics
Divisions:	Faculty of Science > Statistics
Library of Congress Subject Headings (LCSH):	Monte Carlo method, Bayesian statistical decision theory, Filters (Mathematics)
Journal or Publication Title:	Journal of Computational and Graphical Statistics
Publisher:	American Statistical Association
ISSN:	1537-2715
Date:	1 March 2011
Volume:	Vol.20
Number:	No.1
Page Range:	pp. 119-139
Identification Number:	10.1198/jcgs.2009.08052
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Restricted or Subscription Access
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URI:	http://wrap.warwick.ac.uk/id/eprint/37281

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