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In this paper, we consider a general class of two-time-scale Markov chains whose transition rate matrix depends on a parameter $\lambda>0$. We assume that some transition rates of the Markov chain will tend to infinity as…

Probability · Mathematics 2015-07-10 Chen Jia

The distribution of a Markov process with killing, conditioned to be still alive at a given time, can be approximated by a Fleming-Viot type particle system. In such a system, each particle is simulated independently according to the law of…

Probability · Mathematics 2017-09-21 Frederic Cerou , Bernard Delyon , Arnaud Guyader , Mathias Rousset

The first motivation of this paper is to study stationarity and ergodic properties for a general class of time series models defined conditional on an exogenous covariates process. The dynamic of these models is given by an autoregressive…

Statistics Theory · Mathematics 2020-07-16 Paul Doukhan , Michael H. Neumann , Lionel Truquet

We present a sufficient condition for a non-injective function of a Markov chain to be a second-order Markov chain with the same entropy rate as the original chain. This permits an information-preserving state space reduction by merging…

Information Theory · Computer Science 2013-12-20 Bernhard C. Geiger , Christoph Temmel

This paper introduces ergodic-risk criteria, which capture long-term cumulative risks associated with controlled Markov chains through probabilistic limit theorems--in contrast to existing methods that require assumptions of either finite…

Optimization and Control · Mathematics 2025-12-03 Shahriar Talebi , Na Li

It is often possible to speed up the mixing of a Markov chain $\{ X_{t} \}_{t \in \mathbb{N}}$ on a state space $\Omega$ by \textit{lifting}, that is, running a more efficient Markov chain $\{ \hat{X}_{t} \}_{t \in \mathbb{N}}$ on a larger…

Probability · Mathematics 2017-03-01 Kavita Ramanan , Aaron Smith

This review paper provides an introduction of Markov chains and their convergence rates which is an important and interesting mathematical topic which also has important applications for very widely used Markov chain Monte Carlo (MCMC)…

Probability · Mathematics 2021-09-03 Yu Hang Jiang , Tong Liu , Zhiya Lou , Jeffrey S. Rosenthal , Shanshan Shangguan , Fei Wang , Zixuan Wu

In this paper we obtain the central limit theorem for triangular arrays of non-homogeneous Markov chains under a condition imposed to the maximal coefficient of correlation. The proofs are based on martingale techniques and a sharp lower…

Probability · Mathematics 2011-05-24 Magda Peligrad

In this note we prove a spectral gap for various Markov chains on various functional spaces. While proving that a spectral gap exists is relatively common, explicit estimates seems somewhat rare.These estimates are then used to apply the…

Dynamical Systems · Mathematics 2021-02-19 Benoît Kloeckner

We establish that if a sequence of electrical networks equipped with conductance measures converges in the local Gromov--Hausdorff-vague topology and satisfies certain non-explosion and metric-entropy conditions,then the sequence of…

Probability · Mathematics 2025-11-21 Ryoichiro Noda

We consider Markov chains that obey the following general non-linear state space model: $\Phi_{k+1} = F(\Phi_k, \alpha(\Phi_k, U_{k+1}))$ where the function $F$ is $C^1$ while $\alpha$ is typically discontinuous and $\{U_k: k \in…

Probability · Mathematics 2019-02-07 Alexandre Chotard , Anne Auger

We compute some dependence coefficients for the stationary Markov chain whose transition kernel is the Perron-Frobenius operator of an expanding map $T$ of $[0, 1]$ with a neutral fixed point. We use these coefficients to prove a central…

Probability · Mathematics 2008-02-11 J. Dedecker , C. Prieur

We study the convergence rate to stationarity for a class of exchangeable partition-valued Markov chains called cut-and-paste chains. The law governing the transitions of a cut-and-paste chain are determined by products of i.i.d. stochastic…

Probability · Mathematics 2012-09-25 Harry Crane , Steven P. Lalley

The hitting and mixing times are two fundamental quantities associated with Markov chains. In Peres and Sousi[PS2015] and Oliveira[Oli2012], the authors show that the mixing times and "worst-case" hitting times of reversible Markov chains…

Probability · Mathematics 2019-04-05 Robert M. Anderson , Haosui Duanmu , Aaron Smith

The paper presents new asymptotic recurrent algorithms of phase space reduction for regularly and singularly perturbed semi-Markov processes. These algorithms give effective conditions of weak convergence for distributions and convergence…

Probability · Mathematics 2019-07-09 Dmitrii Silvestrov

In this note, the time reversible case of a general theorem of Bhattacharya is shown to imply the Kipnis-Varadhan functional central limit theorem for ergodic Markov processes. To this end, a few results from semigroup theory, including the…

Probability · Mathematics 2026-04-14 Edward C Waymire

We analyze the stationary distribution of regulated Markov modulated Brownian motions (MMBM) modified so that their evolution is slowed down when the process reaches level zero --- level zero is said to be {\em sticky}. To determine the…

Probability · Mathematics 2015-08-06 Guy Latouche , Giang T. Nguyen

Let $(X_t, Y_t)_{t\in T}$ be a discrete or continuous-time Markov process with state space $X \times R^d$ where $X$ is an arbitrary measurable set. Its transition semigroup is assumed to be additive with respect to the second component,…

Probability · Mathematics 2012-07-27 Deborah Ferre , Loïc Hervé , James Ledoux

We study null recurrent renewal Markov chains with renewal distribution in the domain of geometric partial attraction of a semistable law. Using the classical procedure of inversion, we derive a limit theorem similar to the Darling-Kac law…

Dynamical Systems · Mathematics 2018-03-29 Peter Kevei , Dalia Terhesiu

In the present work we derive a Central Limit Theorem for sequences of Hilbert-valued Piecewise Deterministic Markov process models and their global fluctuations around their deterministic limit identified by the Law of Large Numbers. We…

Probability · Mathematics 2013-04-23 Martin G Riedler , Michele Thieullen
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