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    Rights statement: This is the author’s version of a work that was accepted for publication in Statistics and Probability Letters. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Statistics and Probability Letters, 136, 2018 DOI: 10.1016/j.spl.2018.02.021

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Piecewise deterministic Markov processes for scalable Monte Carlo on restricted domains

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Piecewise deterministic Markov processes for scalable Monte Carlo on restricted domains. / Bierkens, Joris; Bouchard-Côté, Alexandre; Doucet, Arnaud et al.

In: Statistics and Probability Letters, Vol. 136, 01.05.2018, p. 148-154.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Bierkens, J, Bouchard-Côté, A, Doucet, A, Duncan, AB, Fearnhead, P, Lienart, T, Roberts, G & Vollmer, SJ 2018, 'Piecewise deterministic Markov processes for scalable Monte Carlo on restricted domains', Statistics and Probability Letters, vol. 136, pp. 148-154. https://doi.org/10.1016/j.spl.2018.02.021

APA

Bierkens, J., Bouchard-Côté, A., Doucet, A., Duncan, A. B., Fearnhead, P., Lienart, T., Roberts, G., & Vollmer, S. J. (2018). Piecewise deterministic Markov processes for scalable Monte Carlo on restricted domains. Statistics and Probability Letters, 136, 148-154. https://doi.org/10.1016/j.spl.2018.02.021

Vancouver

Bierkens J, Bouchard-Côté A, Doucet A, Duncan AB, Fearnhead P, Lienart T et al. Piecewise deterministic Markov processes for scalable Monte Carlo on restricted domains. Statistics and Probability Letters. 2018 May 1;136:148-154. Epub 2018 Mar 2. doi: 10.1016/j.spl.2018.02.021

Author

Bierkens, Joris ; Bouchard-Côté, Alexandre ; Doucet, Arnaud et al. / Piecewise deterministic Markov processes for scalable Monte Carlo on restricted domains. In: Statistics and Probability Letters. 2018 ; Vol. 136. pp. 148-154.

Bibtex

@article{850ef3029b3e478f8fe5dabd932b9c92,
title = "Piecewise deterministic Markov processes for scalable Monte Carlo on restricted domains",
abstract = "Piecewise Deterministic Monte Carlo algorithms enable simulation from a posterior distribution, whilst only needing to access a sub-sample of data at each iteration. We show how they can be implemented in settings where the parameters live on a restricted domain. (C) 2018 Elsevier B.V. All rights reserved.",
keywords = "MCMC, Bayesian statistics, Piecewise deterministic Markov processes, Logistic regression, LEAST-SQUARES",
author = "Joris Bierkens and Alexandre Bouchard-C{\^o}t{\'e} and Arnaud Doucet and Duncan, {Andrew B.} and Paul Fearnhead and Thibaut Lienart and Gareth Roberts and Vollmer, {Sebastian J.}",
note = "This is the author{\textquoteright}s version of a work that was accepted for publication in Statistics and Probability Letters. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Statistics and Probability Letters, 136, 2018 DOI: 10.1016/j.spl.2018.02.021",
year = "2018",
month = may,
day = "1",
doi = "10.1016/j.spl.2018.02.021",
language = "English",
volume = "136",
pages = "148--154",
journal = "Statistics and Probability Letters",
issn = "0167-7152",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Piecewise deterministic Markov processes for scalable Monte Carlo on restricted domains

AU - Bierkens, Joris

AU - Bouchard-Côté, Alexandre

AU - Doucet, Arnaud

AU - Duncan, Andrew B.

AU - Fearnhead, Paul

AU - Lienart, Thibaut

AU - Roberts, Gareth

AU - Vollmer, Sebastian J.

N1 - This is the author’s version of a work that was accepted for publication in Statistics and Probability Letters. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Statistics and Probability Letters, 136, 2018 DOI: 10.1016/j.spl.2018.02.021

PY - 2018/5/1

Y1 - 2018/5/1

N2 - Piecewise Deterministic Monte Carlo algorithms enable simulation from a posterior distribution, whilst only needing to access a sub-sample of data at each iteration. We show how they can be implemented in settings where the parameters live on a restricted domain. (C) 2018 Elsevier B.V. All rights reserved.

AB - Piecewise Deterministic Monte Carlo algorithms enable simulation from a posterior distribution, whilst only needing to access a sub-sample of data at each iteration. We show how they can be implemented in settings where the parameters live on a restricted domain. (C) 2018 Elsevier B.V. All rights reserved.

KW - MCMC

KW - Bayesian statistics

KW - Piecewise deterministic Markov processes

KW - Logistic regression

KW - LEAST-SQUARES

U2 - 10.1016/j.spl.2018.02.021

DO - 10.1016/j.spl.2018.02.021

M3 - Journal article

VL - 136

SP - 148

EP - 154

JO - Statistics and Probability Letters

JF - Statistics and Probability Letters

SN - 0167-7152

ER -