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A tutorial on particle filters

Speekenbrink, M; (2016) A tutorial on particle filters. Journal of Mathematical Psychology , 73 pp. 140-152. 10.1016/j.jmp.2016.05.006. Green open access

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Abstract

This tutorial aims to provide an accessible introduction to particle filters, and sequential Monte Carlo (SMC) more generally. These techniques allow for Bayesian inference in complex dynamic state-space models and have become increasingly popular over the last decades. The basic building blocks of SMC–sequential importance sampling and resampling–are discussed in detail with illustrative examples. A final example presents a particle filter for estimating time-varying learning rates in a probabilistic category learning task.

Type: Article
Title: A tutorial on particle filters
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.jmp.2016.05.006
Publisher version: http://dx.doi.org/10.1016/j.jmp.2016.05.006
Language: English
Additional information: © 2016. This manuscript version is published under a Creative Commons Attribution Non-commercial Non-derivative 4.0 International licence (CC BY-NC-ND 4.0). This licence allows you to share, copy, distribute and transmit the work for personal and non-commercial use providing author and publisher attribution is clearly stated. Further details about CC BY licences are available at http://creativecommons.org/licenses/by/4.0. Access may be initially restricted by the publisher.
Keywords: Particle filter; Sequential Monte Carlo; State-space model; Sequential Bayesian inference
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > Div of Psychology and Lang Sciences > Experimental Psychology
URI: http://discovery.ucl.ac.uk/id/eprint/1508064
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