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On blocks, tempering and particle MCMC for systems identification

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Johansen, Adam M. (2015) On blocks, tempering and particle MCMC for systems identification. In: 17th IFAC Symposium on System Identification, Beijing, China, 19-21 Oct 2015. Published in: IFAC-PapersOnLine, 48 (28). pp. 969-974. doi:10.1016/j.ifacol.2015.12.256

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Official URL: https://doi.org/10.1016/j.ifacol.2015.12.256

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Abstract

The widespread use of particle methods for addressing the filtering and smoothing problems in state-space models has, in recent years, been complemented by the development of particle Markov Chain Monte Carlo (PMCMC) methods. PMCMC uses particle filters within offline systems-identification settings. We develop a modified particle filter, based around block sampling and tempering, intended to improve their exploration of the state space and the associated estimation of the marginal likelihood. The aim is to develop particle methods with improved robustness properties, particularly for parameter values which are not able to explain observed data well, for use within PMCMC algorithms. The proposed strategies do not require a substantial analytic understanding of the model structure, unlike most techniques for improving particle-filter performance.

Item Type: Conference Item (Paper)
Alternative Title:
Subjects: Q Science > QA Mathematics
Divisions: Faculty of Science > Statistics
Library of Congress Subject Headings (LCSH): Monte Carlo method, Dynamics
Journal or Publication Title: IFAC-PapersOnLine
Publisher: Elsevier
Official Date: 25 December 2015
Dates:
DateEvent
25 December 2015Published
Volume: 48
Number: 28
Page Range: pp. 969-974
DOI: 10.1016/j.ifacol.2015.12.256
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Conference Paper Type: Paper
Title of Event: 17th IFAC Symposium on System Identification
Type of Event: Conference
Location of Event: Beijing, China
Date(s) of Event: 19-21 Oct 2015
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