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Simulation from quasi-stationary distributions on reducible state spaces

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Griffin, Adam, Jenkins, Paul, Roberts, Gareth O. and Spencer, Simon E. F. (2017) Simulation from quasi-stationary distributions on reducible state spaces. Advances in Applied Probability, 49 (3). pp. 960-980. doi:10.1017/apr.2017.28

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Official URL: https://doi.org/10.1017/apr.2017.28

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Abstract

Quasi-stationary distributions (QSDs) arise from stochastic processes that exhibit transient equilibrium behaviour on the way to absorption. QSDs are often mathematically intractable and even drawing samples from them is not straightforward. In this paper the framework of Sequential Monte Carlo samplers is utilized to simulate QSDs and several novel resampling techniques are proposed to accommodate models with reducible state spaces, with particular focus on preserving particle diversity on discrete spaces. Finally an approach is considered to estimate eigenvalues associated with QSDs, such as the decay parameter.

Item Type: Journal Article
Subjects: Q Science > QA Mathematics
Divisions: Faculty of Science > Mathematics
Faculty of Science > Statistics
Library of Congress Subject Headings (LCSH): Resampling (Statistics), Stochastic analysis, Monte Carlo method
Journal or Publication Title: Advances in Applied Probability
Publisher: Applied Probability Trust
ISSN: 0001-8678
Official Date: 8 September 2017
Dates:
DateEvent
8 September 2017Available
18 May 2017Accepted
Volume: 49
Number: 3
Page Range: pp. 960-980
DOI: 10.1017/apr.2017.28
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
EP/HO23364/1Engineering and Physical Sciences Research Councilhttp://dx.doi.org/10.13039/501100000266
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  • http://www.appliedprobability.org/

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