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Related papers: Ergodicity for the $GI/G/1$-type Markov Chain

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For a discrete-time Markov chain $\{X(t)\}$ evolving on $\Re^\ell$ with transition kernel $P$, natural, general conditions are developed under which the following are established: 1. The transition kernel $P$ has a purely discrete spectrum,…

Probability · Mathematics 2019-07-19 Adithya Devraj , Ioannis Kontoyiannis , Sean Meyn

We establish verifiable general sufficient conditions for exponential or subexponential ergodicity of Markov processes that may lack the strong Feller property. We apply the obtained results to show exponential ergodicity of a variety of…

Probability · Mathematics 2019-03-27 Oleg Butkovsky , Alexei Kulik , Michael Scheutzow

We prove that an irreducible aperiodic Markov chain is geometrically ergodic if and only if any separately bounded functional of the stationary chain satisfies an appropriate subgaussian deviation inequality from its mean.

Probability · Mathematics 2015-07-22 Jérôme Dedecker , Sébastien Gouëzel

In this work, we consider an inhomogeneous (discrete time) Markov chain and are interested in its long time behavior. We provide sufficient conditions to ensure that some of its asymptotic properties can be related to the ones of a…

Probability · Mathematics 2017-11-09 Michel Benaïm , Florian Bouguet , Bertrand Cloez

This paper provides a new path method that can be used to determine when an ergodic continuous-time Markov chain on $\mathbb Z^d$ converges exponentially fast to its stationary distribution in $L^2$. Specifically, we provide general…

Probability · Mathematics 2023-10-02 David F. Anderson , Daniele Cappelletti , Wai-Tong Louis Fan , Jinsu Kim

In this short note we prove ``effective" geometric ergodicity (i.e a Perron-Frobenius theorem) for Markov chains in random mixing dynamical environment satisfying a random non-uniform version of the Doeblin condition. Effectivity here means…

Probability · Mathematics 2026-01-05 Yeor Hafouta

Necessary and sufficient conditions for a Markov chain to be ergodic are that the chain is irreducible and aperiodic. This result is manifest in the case of random walks on finite groups by a statement about the support of the driving…

Quantum Algebra · Mathematics 2021-10-22 J. P. McCarthy

We consider a discrete time hidden Markov model where the signal is a stationary Markov chain. When conditioned on the observations, the signal is a Markov chain in a random environment under the conditional measure. It is shown that this…

Probability · Mathematics 2009-09-24 Ramon van Handel

For affine processes on finite-dimensional cones, we give criteria for geometric ergodicity - that is exponentially fast convergence to a unique stationary distribution. Ergodic results include both the existence of exponential moments of…

Probability · Mathematics 2021-01-12 Eberhard Mayerhofer , Robert Stelzer , Johanna Vestweber

Improved rates of convergence for ergodic homogeneous Markov chains are studied. In comparison to the earlier papers the setting is also generalised to the case without a unique dominated measure. Examples are provided where the new bound…

Probability · Mathematics 2021-11-02 Alexander Veretennikov , Maria Veretennikova

This article studies the convergence properties of trans-dimensional MCMC algorithms when the total number of models is finite. It is shown that, for reversible and some non-reversible trans-dimensional Markov chains, under mild conditions,…

Statistics Theory · Mathematics 2024-10-18 Qian Qin

It is known that Dobrushin's ergodicity coefficient is one of the effective tools in the investigations of limiting behavior of Markov processes. Several interesting properties of the ergodicity coefficient of a positive mapping defined on…

Functional Analysis · Mathematics 2017-04-26 Nazife Erkurşun Özcan , Farrukh Mukhamedov

Conditions for the existence of strictly stationary multivariate GARCH processes in the so-called BEKK parametrisation, which is the most general form of multivariate GARCH processes typically used in applications, and for their geometric…

Probability · Mathematics 2011-08-02 Farid Boussama , Florian Fuchs , Robert Stelzer

Improved rates of convergence for ergodic Markov chains and relaxed conditions for them, as well as analogous convergence results for some non-homogeneous Markov chains are studied. The setting from the previous works is extended. Examples…

Probability · Mathematics 2022-09-27 A. Yu. Veretennikov , M. A. Veretennikova

We study a class of dynamical systems generated by random substitutions, which contains both intrinsically ergodic systems and instances with several measures of maximal entropy. In this class, we show that the measures of maximal entropy…

Dynamical Systems · Mathematics 2026-03-26 Philipp Gohlke , Andrew Mitchell

The class of nonlinear Markov processes is characterized by the dependence of the current state of the process on its current distribution in addition to the dependence on the previous state. Due to this feature, these processes are…

Probability · Mathematics 2022-12-27 Aleksandr Shchegolev

In this article, we discuss ergodicity properties of a diffusion process given through an It\^{o} stochastic differential equation. We identify conditions on the drift and diffusion coefficients which result in sub-geometric ergodicity of…

Probability · Mathematics 2020-06-03 Petra Lazić , Nikola Sandrić

We study the ergodic properties of two classes of random dynamical systems: a type of Markov chain which we call the \textit{alternating random walk} and a certain stochastic billiard system which describes the motion of a free-moving rough…

Dynamical Systems · Mathematics 2024-01-02 Peter Rudzis

We exhibit an efficient procedure for testing, based on a single long state sequence, whether an unknown Markov chain is identical to or $\varepsilon$-far from a given reference chain. We obtain nearly matching (up to logarithmic factors)…

Machine Learning · Statistics 2019-09-26 Geoffrey Wolfer , Aryeh Kontorovich

Recent research has shown the potential utility of Deep Gaussian Processes. These deep structures are probability distributions, designed through hierarchical construction, which are conditionally Gaussian. In this paper, the current…

Statistics Theory · Mathematics 2018-08-20 Matthew M. Dunlop , Mark A. Girolami , Andrew M. Stuart , Aretha L. Teckentrup