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Particle filtering
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Johansen, Adam M. (2019) Particle filtering. In: Balakrishnan, N. and Colton, T. and Everitt, B. and Piegorsch, W. and Ruggeri, F. and Teugels, J. L., (eds.) Wiley StatsRef: Statistics Reference Online. Wiley. ISBN 9781118445112
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Official URL: https://doi.org/10.1002/9781118445112.stat08207
Abstract
Particle filtering is a (sequential) Monte Carlo technique for simulation‐based inference in intractable general state space hidden Markov models for which such inference is not analytically tractable. It is an approach to characterize the distribution of an indirectly observed Markov chain as observations become available, which involves simulating the evolution of a system of particles, which can be used to approximate estimators of interest.
Item Type: | Book Item | ||||||
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | ||||||
Publisher: | Wiley | ||||||
ISBN: | 9781118445112 | ||||||
Book Title: | Wiley StatsRef: Statistics Reference Online | ||||||
Editor: | Balakrishnan, N. and Colton, T. and Everitt, B. and Piegorsch, W. and Ruggeri, F. and Teugels, J. L. | ||||||
Official Date: | 9 May 2019 | ||||||
Dates: |
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DOI: | 10.1002/9781118445112.stat08207 | ||||||
Status: | Peer Reviewed | ||||||
Publication Status: | Published | ||||||
Date of first compliant deposit: | 28 September 2018 |
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