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- W3201964295 abstract "Historically time-reversibility of the transitions or processes underpinning Markov chain Monte Carlo methods (MCMC) has played a key role in their development, while the self-adjointness of associated operators together with the use of classical functional analysis techniques on Hilbert spaces have led to powerful and practically successful tools to characterise and compare their performance. Similar results for algorithms relying on nonreversible Markov processes are scarce. We show that for a type of nonreversible Monte Carlo Markov chains and processes, of current or renewed interest in the physics and statistical literatures, it is possible to develop comparison results which closely mirror those available in the reversible scenario. We show that these results shed light on earlier literature, proving some conjectures and strengthening some earlier results." @default.
- W3201964295 created "2021-10-11" @default.
- W3201964295 creator A5027207498 @default.
- W3201964295 creator A5077007118 @default.
- W3201964295 date "2021-08-01" @default.
- W3201964295 modified "2023-10-16" @default.
- W3201964295 title "Peskun–Tierney ordering for Markovian Monte Carlo: Beyond the reversible scenario" @default.
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- W3201964295 doi "https://doi.org/10.1214/20-aos2008" @default.
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