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Zig-zag sampling for discrete structures and non-reversible phylogenetic MCMC
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Koskela, Jere (2022) Zig-zag sampling for discrete structures and non-reversible phylogenetic MCMC. Journal of Computational and Graphical Statistics, 31 (3). pp. 684-694. doi:10.1080/10618600.2022.2032722 ISSN 1061-8600.
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WRAP-Zig-zag-sampling-discrete-structures-non-reversible-phylogenetic-MCMC-Koskela-2022.pdf - Accepted Version - Requires a PDF viewer. Download (1769Kb) | Preview |
Official URL: https://doi.org/10.1080/10618600.2022.2032722
Abstract
We construct a zig-zag process targeting a posterior distribution defined on a hybrid state space consisting of both discrete and continuous variables. The construction does not require any assumptions on the structure among discrete variables. We demonstrate our method on two examples in genetics based on the Kingman coalescent, showing that the zig-zag process can lead to efficiency gains of up to several orders of magnitude over classical Metropolis– Hastings algorithms, and that it is well suited to parallel computation. Our construction resembles existing techniques for Hamiltonian Monte Carlo on a hybrid state space, which suffers from implementationally and analytically complex boundary crossings when applied to the coalescent. We demonstrate that the continuous-time zig-zag process avoids these complications.
Item Type: | Journal Article | ||||||
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Subjects: | Q Science > QA Mathematics | ||||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Statistics | ||||||
Library of Congress Subject Headings (LCSH): | Markov processes, Monte Carlo method, Sampling (Statistics), Bayesian statistical decision theory | ||||||
Journal or Publication Title: | Journal of Computational and Graphical Statistics | ||||||
Publisher: | American Statistical Association | ||||||
ISSN: | 1061-8600 | ||||||
Official Date: | 25 January 2022 | ||||||
Dates: |
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Volume: | 31 | ||||||
Number: | 3 | ||||||
Page Range: | pp. 684-694 | ||||||
DOI: | 10.1080/10618600.2022.2032722 | ||||||
Status: | Peer Reviewed | ||||||
Publication Status: | Published | ||||||
Reuse Statement (publisher, data, author rights): | This is an Accepted Manuscript of an article published by Taylor & Francis in Journal of Computational and Graphical Statistics on 25/02/2022, available online: http://www.tandfonline.com/10.1080/10618600.2022.2032722 | ||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||
Date of first compliant deposit: | 19 January 2022 | ||||||
Date of first compliant Open Access: | 25 January 2023 | ||||||
RIOXX Funder/Project Grant: |
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