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Piecewise-deterministic Markov chain Monte Carlo

Abstract:

Recent interest in a class of Markov chain Monte Carlo schemes based on continuous-time piecewise-deterministic Markov processes has led to several new and promising algorithmic developments. Prominent examples include the zig-zag process and the bouncy particle sampler. We explore this class of algorithms, proposing extensions and drawing connections to existing literature.

Two key aspects of a continuous-time piecewise-deterministic process are the flow and the event kernel

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Division:
MPLS
Department:
Statistics
Role:
Author

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Role:
Supervisor
ORCID:
0000-0002-7662-419X
Type of award:
DPhil
Level of award:
Doctoral
Awarding institution:
University of Oxford

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