On ergodicity and transience for a class of level-dependent GI/M/1-type Markov chains

Abstract We investigate a specific class of irreducible, level-dependent, discrete-time, GI/M/1-type Markov chains. The transition matrices possess a block lower-Hessenberg structure, which shows asymptotic convergence along the rows as the level approaches infinity. Criteria are presented for recurrence, transience, positive recurrence, geometric ergodicity, and geometric transience in terms of elements of the transition matrices. These criteria are established by employing drift functions and matrix-generating functions. Furthermore, we discuss the extension of the main results to the continuous-time case.

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Publication Details

Journal
Journal of Applied Probability
Published
2025-11-21
DOI
https://doi.org/10.1017/jpr.2025.10
Primary Topic
Markov Chains and Monte Carlo Methods
Type
article
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article

On ergodicity and transience for a class of level-dependent GI/M/1-type Markov chains

Yuanyuan Liu, Fangfang Lyu
Journal of Applied Probability
Markov Chains and Monte Carlo Methods
article

On ergodicity and transience for a class of level-dependent GI/M/1-type Markov chains

Yuanyuan Liu, Fangfang Lyu
article en

Abstract

Abstract We investigate a specific class of irreducible, level-dependent, discrete-time, GI/M/1-type Markov chains. The transition matrices possess a block lower-Hessenberg structure, which shows asymptotic convergence along the rows as the level approaches infinity. Criteria are presented for recurrence, transience, positive recurrence, geometric ergodicity, and geometric transience in terms of elements of the transition matrices. These criteria are established by employing drift functions and matrix-generating functions. Furthermore, we discuss the extension of the main results to the continuous-time case.

Journal of Applied ProbabilityVol. 62(4)
Central South University (CN)
Openalex Percentile: Top 67%
Markov Chains and Monte Carlo Methods
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