|
This article is cited in 3 scientific papers (total in 4 papers)
On improved bounds and conditions for the convergence of Markov chains
A. Yu. Veretennikovab, M. A. Veretennikovac a Institute for Information Transmission Problems of the Russian Academy of Sciences (Kharkevich Institute), Moscow
b National Research University "Higher School of Economics", Moscow
c The Zeeman Institute, University of Warwick, United Kingdom
Abstract:
We continue the work of improving the rate of convergence of ergodic homogeneous
Markov chains. The setting is more general than in previous papers: we are able to get rid
of the assumption about a common dominating measure and consider the case of inhomogeneous
Markov chains as well as more general state spaces. We give examples where the new bound
for the rate of convergence is the same as (resp. better than) the classical Markov–Dobrushin
inequality.
Keywords:
Markov chains, ergodicity, generalization of the Markov–Dobrushin condition, rate of convergence.
Received: 23.06.2020 Revised: 09.08.2020
Citation:
A. Yu. Veretennikov, M. A. Veretennikova, “On improved bounds and conditions for the convergence of Markov chains”, Izv. RAN. Ser. Mat., 86:1 (2022), 98–133; Izv. Math., 86:1 (2022), 92–125
Linking options:
https://www.mathnet.ru/eng/im9076https://doi.org/10.1070/IM9076 https://www.mathnet.ru/eng/im/v86/i1/p98
|
Statistics & downloads: |
Abstract page: | 418 | Russian version PDF: | 78 | English version PDF: | 43 | Russian version HTML: | 205 | References: | 83 | First page: | 25 |
|