Uniform Wasserstein convergence of penalized Markov processes
Fuente:
arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2023
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| Soggetti: | |
| Accesso online: | |
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| _version_ | 1866912702476058624 |
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| author | Champagnat, Nicolas Strickler, Edouard Villemonais, Denis |
| author_facet | Champagnat, Nicolas Strickler, Edouard Villemonais, Denis |
| contents | For general penalized Markov processes with soft killing, we propose a simple criterion ensuring uniform convergence of conditional distributions in Wasserstein distance to a unique quasi-stationary distribution. We give several examples of application where our criterion can be checked, including Bernoulli convolutions and piecewise deterministic Markov processes of the form of switched dynamical systems, for which convergence in total variation is not possible. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2306_16051 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Uniform Wasserstein convergence of penalized Markov processes Champagnat, Nicolas Strickler, Edouard Villemonais, Denis Probability For general penalized Markov processes with soft killing, we propose a simple criterion ensuring uniform convergence of conditional distributions in Wasserstein distance to a unique quasi-stationary distribution. We give several examples of application where our criterion can be checked, including Bernoulli convolutions and piecewise deterministic Markov processes of the form of switched dynamical systems, for which convergence in total variation is not possible. |
| title | Uniform Wasserstein convergence of penalized Markov processes |
| topic | Probability |
| url | https://arxiv.org/abs/2306.16051 |