On some basic features of strictly stationary, reversible Markov chains

DOI10.1111/jtsa.12583zbMath1477.60111OpenAlexW3120605771MaRDI QIDQ5012851

Richard C. jun. Bradley

Publication date: 25 November 2021

Published in: Journal of Time Series Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/jtsa.12583

zbMATH Keywords

strong mixingspectral gap conditiongeometric ergodicityreversible Markov chainstrictly stationary

Mathematics Subject Classification ID

Stationary stochastic processes (60G10) Markov chains (discrete-time Markov processes on discrete state spaces) (60J10)

Cites Work

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• Some aspects of modeling dependence in copula-based Markov chains
• Information regularity and the central limit question
• Geometric ergodicity of Harris recurrent Markov chains with applications to renewal theory
• Geometric ergodicity and R-positivity for general Markov chains
• On quantiles and the central limit question for strongly mixing sequences
• Geometric ergodicity and hybrid Markov chains
• On the central limit theorem for geometrically ergodic Markov chains
• Geometric ergodicity and the spectral gap of non-reversible Markov chains
• Remarks on limit theorems for reversible Markov processes and their applications
• Remarks on the speed of convergence of mixing coefficients and applications
• On Mixing Properties of Reversible Markov Chains
• Geometric L² and ^{L1 convergence are equivalent for reversible Markov chains}
• A CENTRAL LIMIT THEOREM AND A STRONG MIXING CONDITION
• Some Limit Theorems for Random Functions. I
• GEOMETRIC ERGODICITY IN DENUMERABLE MARKOV CHAINS
• On Strong Mixing Conditions for Stationary Gaussian Processes
• Markov Chains and Stochastic Stability
• On dependence structure of copula-based Markov chains
• Copulas and Temporal Dependence

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