Uniform Wasserstein convergence of penalized Markov processes

Fuente: arXiv
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Autori principali: Champagnat, Nicolas, Strickler, Edouard, Villemonais, Denis
Natura: Preprint
Pubblicazione: 2023
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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