Convergence of Markov chain transition probabilities

Fuente: arXiv
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Main Authors: Scheutzow, Michael, Schindler, Juni
Format: Preprint
Published: 2020
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author Scheutzow, Michael
Schindler, Juni
author_facet Scheutzow, Michael
Schindler, Juni
contents Consider a discrete time Markov chain with rather general state space which has an invariant probability measure $μ$. There are several sufficient conditions in the literature which guarantee convergence of all or $μ$-almost all transition probabilities to $μ$ in the total variation (TV) metric: irreducibility plus aperiodicity, equivalence properties of transition probabilities, or coupling properties. In this work, we review and improve some of these criteria in such a way that they become necessary and sufficient for TV convergence of all respectively $μ$-almost all transition probabilities. In addition, we discuss so-called generalized couplings.
format Preprint
id arxiv_https___arxiv_org_abs_2004_10235
institution arXiv
publishDate 2020
record_format arxiv
spellingShingle Convergence of Markov chain transition probabilities
Scheutzow, Michael
Schindler, Juni
Probability
Primary 60J05, Secondary 60G10
Consider a discrete time Markov chain with rather general state space which has an invariant probability measure $μ$. There are several sufficient conditions in the literature which guarantee convergence of all or $μ$-almost all transition probabilities to $μ$ in the total variation (TV) metric: irreducibility plus aperiodicity, equivalence properties of transition probabilities, or coupling properties. In this work, we review and improve some of these criteria in such a way that they become necessary and sufficient for TV convergence of all respectively $μ$-almost all transition probabilities. In addition, we discuss so-called generalized couplings.
title Convergence of Markov chain transition probabilities
topic Probability
Primary 60J05, Secondary 60G10
url https://arxiv.org/abs/2004.10235