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There are many Markov chains on infinite dimensional spaces whose one-step transition kernels are mutually singular when starting from different initial conditions. We give results which prove unique ergodicity under minimal assumptions on…

Probability · Mathematics 2009-08-20 Martin Hairer , Jonathan C. Mattingly , Michael Scheutzow

We prove an ergodic theorem for Markov chains indexed by the Ulam-Harris-Neveu tree over large subsets with arbitrary shape under two assumptions: with high probability, two vertices in the large subset are far from each other and have…

Probability · Mathematics 2026-03-11 Julien Weibel

This paper is a survey of various proofs of the so called {\em fundamental theorem of Markov chains}: every ergodic Markov chain has a unique positive stationary distribution and the chain attains this distribution in the limit independent…

Probability · Mathematics 2022-04-05 Somenath Biswas

We argue that the spectral theory of non-reversible Markov chains may often be more effectively cast within the framework of the naturally associated weighted-$L_\infty$ space $L_\infty^V$, instead of the usual Hilbert space $L_2=L_2(\pi)$,…

Probability · Mathematics 2009-06-30 Ioannis Kontoyiannis , Sean P. Meyn

The goal of this paper is to develop a general method to establish conditional ergodicity of infinite-dimensional Markov chains. Given a Markov chain in a product space, we aim to understand the ergodic properties of its conditional…

Probability · Mathematics 2014-10-28 Xin Thomson Tong , Ramon van Handel

For a Markov chain $Y$ with values in a Polish space, consider the entrance Markov chain obtained by sampling $Y$ at the moments when it enters a fixed set $A$ from its complement $A^c$. Similarly, consider the exit Markov chain, obtained…

Probability · Mathematics 2020-05-25 Aleksandar Mijatović , Vladislav Vysotsky

For a Markov chain $Y$ with values in a Polish space, consider the entrance chain, obtained by sampling $Y$ at the moments when it enters a fixed set $A$ from its complement $A^c$. Similarly, consider the exit chain, obtained by sampling…

Probability · Mathematics 2025-05-15 Aleksandar Mijatovic , Vladislav Vysotsky

Applying quantitative perturbation theory for linear operators, we prove non-asymptotic limit theorems for Markov chains whose transition kernel has a spectral gap in an arbitrary Banach algebra of functions X . The main results are…

Probability · Mathematics 2018-10-31 Benoît Kloeckner

Consider the partial sums {S_t} of a real-valued functional F(Phi(t)) of a Markov chain {Phi(t)} with values in a general state space. Assuming only that the Markov chain is geometrically ergodic and that the functional F is bounded, the…

Probability · Mathematics 2007-05-23 Ioannis Kontoyiannis , Sean Meyn

In the framework of statistical mechanics the properties of macroscopic systems are deduced starting from the laws of their microscopic dynamics. One of the key assumptions in this procedure is the ergodic property, namely the equivalence…

Statistical Mechanics · Physics 2024-01-09 Marco Baldovin , Raffaele Marino , Angelo Vulpiani

We consider general Markov chains with discrete time in an arbitrary measurable (phase) space and homogeneous in time. Markov chains are defined by the classical transition function which within the framework of the operator treatment…

Probability · Mathematics 2020-06-17 Alexander I. Zhdanok

Given access to a single long trajectory generated by an unknown irreducible Markov chain $M$, we simulate an $\alpha$-lazy version of $M$ which is ergodic. This enables us to generalize recent results on estimation and identity testing…

Machine Learning · Statistics 2021-11-02 Sela Fried , Geoffrey Wolfer

We study ergodic properties of nonlinear Markov chains and stochastic McKean-Vlasov equations. For nonlinear Markov chains we obtain sufficient conditions for existence and uniqueness of an invariant measure and uniform ergodicity. We also…

Probability · Mathematics 2013-11-26 Oleg Butkovsky

The purpose of this paper is to study the time average behavior of Markov chains with transition probabilities being kernels of completely continuous operators, and therefore to provide a sufficient condition for a class of Markov chains…

Probability · Mathematics 2018-11-16 Shizhou Xu

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

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

We investigate and prove the mathematical properties of a general class of one-dimensional unimodal smooth maps perturbed with a heteroscedastic noise. Specifically, we investigate the stability of the associated Markov chain, show the weak…

Dynamical Systems · Mathematics 2023-05-24 F. Lillo , G. Livieri , S. Marmi , A. Solomko , S. Vaienti

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 consider Markov chain with spectral gap in $L^2$ space. Assume that $f$ is a bounded function. Then the probabilities of large deviations of average along trajectory satisfy Hoeffding's-type inequalities. These bounds depend only on the…

Probability · Mathematics 2013-06-14 Błażej Miasojedow

Perturbation theory for Markov chains addresses the question how small differences in the transitions of Markov chains are reflected in differences between their distributions. We prove powerful and flexible bounds on the distance of the…

Computation · Statistics 2017-02-27 Daniel Rudolf , Nikolaus Schweizer
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