Polynomial Convergence Rates of Piecewise Deterministic Markov Processes-Reference-Cited by-同舟云学术

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Polynomial Convergence Rates of Piecewise Deterministic Markov Processes

Published:2023-01-31 Issue:1 Volume:25 Page:
ISSN:1387-5841
Container-title:Methodology and Computing in Applied Probability
language:en
Short-container-title:Methodol Comput Appl Probab

Author:

Roberts Gareth O.,Rosenthal Jeffrey S.

Funder

EPSRC

Natural Sciences and Engineering Research Council of Canada

Publisher

Springer Science and Business Media LLC

Subject

General Mathematics,Statistics and Probability

Link

https://link.springer.com/content/pdf/10.1007/s11009-023-09977-2.pdf

Reference17 articles.

1. Andrieu C, Dobson P, Wang AQ (2021a) Subgeometric hypocoercivity for piecewise-deterministic Markov process Monte Carlo methods. Elec J Prob 26:1–26

2. Andrieu C, Durmus A, Nüsken N, Roussel J (2021b) Hypocoercivity of piecewise deterministic Markov process-Monte Carlo. Ann Appl Prob 31(5):2478–2517

3. Bierkens J (2021) Piecewise deterministic Monte Carlo web resource page. https://diamweb.ewi.tudelft.nl/~joris/pdmps.html

4. Bierkens J, Fearnhead P, Roberts GO (2019) The Zig-Zag process and super-efficient sampling for Bayesian analysis of big data. Ann Stat 47(3):1288–1320

5. Bierkens J, Roberts GO, Zitt PA (2019) Ergodicity of the zigzag process. Ann Appl Prob 29(4):2266–2301

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