State-dependent criteria for convergence of Markov chains
type: Item
instance of: scholarly article
title: State-dependent criteria for convergence of Markov chains
zbMATH Open document ID: 0803.60060
published in: The Annals of Applied Probability
publication date: 1995-01-03T00:00:00Z
review text: By using state-dependent step mean drift (and random-step) conditions, criteria for Harris recurrence, positive recurrence and geometric ergodicity are obtained for time-discrete Markov chains on general state spaces. This extends the classical Foster-Lyapunov approach for denumerable Markov chains [see the authors, Markov chains and stochastic stability (Springer, 1993) and \textit{V. A. Malyshev} and \textit{M. V. Men'shikov}, Trans. Mosc. Math. Soc. 1981, No. 1, 1-48 (1981); translation from Tr. Mosk. Mat. O.-va 39, 3-48 (1979; Zbl 0441.60073)]. Applications to antibody activity, to nonlinear threshold autoregression and to complex queueing models are provided.
Mathematics Subject Classification ID: 60J10
Mathematics Subject Classification ID: 60J20
zbMATH DE Number: 591424
zbMATH Keywords: Harris recurrence
zbMATH Keywords: positive recurrence
zbMATH Keywords: geometric ergodicity
zbMATH Keywords: Foster- Lyapunov approach
zbMATH Keywords: antibody activity
zbMATH Keywords: nonlinear threshold autoregression
zbMATH Keywords: complex queueing models
author: Sean P. Meyn
author: R. L. Tweedie
reviewed by: Minping Qian
MaRDI profile type: Publication
full work available at URL: https://doi.org/10.1214/aoap/1177005204
OpenAlex ID: W2171923726
DOI: 10.1214/AOAP/1177005204
description: scientific article; zbMATH DE number 591424