Regeneration-enriched Markov processes with application to Monte Carlo
We study a class of Markov processes that combine local dynamics, arising from a fixed Markov process, with regenerations arising at a state-dependent rate. We give conditions under which such processes possess a given target distribution as their invariant measures, thus making them amenable for us...
| Main Authors: | , , , |
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| Format: | Journal article |
| Language: | English |
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Institute of Mathematical Statistics
2021
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| _version_ | 1797062110128111616 |
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| author | Wang, AQ Pollock, M Roberts, GO Steinsaltz, D |
| author_facet | Wang, AQ Pollock, M Roberts, GO Steinsaltz, D |
| author_sort | Wang, AQ |
| collection | OXFORD |
| description | We study a class of Markov processes that combine local dynamics, arising from a fixed Markov process, with regenerations arising at a state-dependent rate. We give conditions under which such processes possess a given target distribution as their invariant measures, thus making them amenable for use within Monte Carlo methodologies. Since the regeneration mechanism can compensate the choice of local dynamics, while retaining the same invariant distribution, great flexibility can be achieved in selecting local dynamics, and the mathematical analysis is simplified. We give straightforward conditions for the process to possess a central limit theorem, and additional conditions for uniform ergodicity and for a coupling from the past construction to hold, enabling exact sampling from the invariant distribution. We further consider and analyse a natural approximation of the process which may arise in the practical simulation of some classes of continuous-time dynamics. |
| first_indexed | 2024-03-06T20:40:52Z |
| format | Journal article |
| id | oxford-uuid:343badd9-b7bf-4ac9-9793-de214c96e17d |
| institution | University of Oxford |
| language | English |
| last_indexed | 2024-03-06T20:40:52Z |
| publishDate | 2021 |
| publisher | Institute of Mathematical Statistics |
| record_format | dspace |
| spelling | oxford-uuid:343badd9-b7bf-4ac9-9793-de214c96e17d2022-03-26T13:24:45ZRegeneration-enriched Markov processes with application to Monte CarloJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:343badd9-b7bf-4ac9-9793-de214c96e17dEnglishSymplectic ElementsInstitute of Mathematical Statistics2021Wang, AQPollock, MRoberts, GOSteinsaltz, DWe study a class of Markov processes that combine local dynamics, arising from a fixed Markov process, with regenerations arising at a state-dependent rate. We give conditions under which such processes possess a given target distribution as their invariant measures, thus making them amenable for use within Monte Carlo methodologies. Since the regeneration mechanism can compensate the choice of local dynamics, while retaining the same invariant distribution, great flexibility can be achieved in selecting local dynamics, and the mathematical analysis is simplified. We give straightforward conditions for the process to possess a central limit theorem, and additional conditions for uniform ergodicity and for a coupling from the past construction to hold, enabling exact sampling from the invariant distribution. We further consider and analyse a natural approximation of the process which may arise in the practical simulation of some classes of continuous-time dynamics. |
| spellingShingle | Wang, AQ Pollock, M Roberts, GO Steinsaltz, D Regeneration-enriched Markov processes with application to Monte Carlo |
| title | Regeneration-enriched Markov processes with application to Monte Carlo |
| title_full | Regeneration-enriched Markov processes with application to Monte Carlo |
| title_fullStr | Regeneration-enriched Markov processes with application to Monte Carlo |
| title_full_unstemmed | Regeneration-enriched Markov processes with application to Monte Carlo |
| title_short | Regeneration-enriched Markov processes with application to Monte Carlo |
| title_sort | regeneration enriched markov processes with application to monte carlo |
| work_keys_str_mv | AT wangaq regenerationenrichedmarkovprocesseswithapplicationtomontecarlo AT pollockm regenerationenrichedmarkovprocesseswithapplicationtomontecarlo AT robertsgo regenerationenrichedmarkovprocesseswithapplicationtomontecarlo AT steinsaltzd regenerationenrichedmarkovprocesseswithapplicationtomontecarlo |