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The bouncy particle sampler: A non-reversible rejection free Markov chain Monte Carlo method

Abstract:

Many Markov chain Monte Carlo techniques currently available rely on discrete-time reversible Markov processes whose transition kernels are variations of the Metropolis–Hastings algorithm. We explore and generalize an alternative scheme recently introduced in the physics literature where the target distribution is explored using a continuous-time non-reversible piecewise-deterministic Markov process. In the Metropolis–Hastings algorithm, a trial move to a region of lower target density, equiv...

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Publication status:
Published
Peer review status:
Peer reviewed
Version:
Accepted manuscript

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Publisher copy:
10.1080/01621459.2017.1294075

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Department:
Hertford College
Vollmer, SJ More by this author
Bouchard-Cote, A More by this author
Publisher:
Taylor & Francis Publisher's website
Journal:
Journal of the American Statistical Association Journal website
Volume:
113
Issue:
522
Pages:
855-867
Publication date:
2017-02-28
Acceptance date:
2017-01-06
DOI:
EISSN:
1537-274X
ISSN:
0162-1459
Pubs id:
pubs:679244
URN:
uri:301047da-e7f2-4cd7-9026-fdd5c3046903
UUID:
uuid:301047da-e7f2-4cd7-9026-fdd5c3046903
Local pid:
pubs:679244

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