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We study normal approximations for a class of discrete-time occupancy processes, namely, Markov chains with transition kernels of product Bernoulli form. This class encompasses numerous models which appear in the complex networks…

Probability · Mathematics 2018-11-13 Liam Hodgkinson , Ross McVinish , Philip K. Pollett

We introduce a unified operator-theoretic framework for analyzing mixing times of finite-state ergodic Markov chains that applies to both reversible and non-reversible dynamics. The central object in our analysis is the projected transition…

Probability · Mathematics 2025-11-05 Muhammad Abdullah Naeem

The formal verification of large probabilistic models is important and challenging. Exploiting the concurrency that is often present is one way to address this problem. Here we study a restricted class of asynchronous distributed…

Distributed, Parallel, and Cluster Computing · Computer Science 2014-08-06 Sumit Kumar Jha , Madhavan Mukund , Ratul Saha , P S Thiagarajan

For a reversible and ergodic Markov chain $\{X_n,n\geq0\}$ with invariant distribution $\pi$, we show that a valid confidence interval for $\pi(h)$ can be constructed whenever the asymptotic variance $\sigma^2_P(h)$ is finite and positive.…

Statistics Theory · Mathematics 2016-08-14 Yves F. Atchadé

We consider Markov chains with random transition probabilities which, moreover, fluctuate randomly with time. We describe such a system by a product of stochastic matrices, $U(t)=M_t\cdots M_1$, with the factors $M_i$ drawn independently…

Mathematical Physics · Physics 2018-11-14 G. C. P. Innocentini , M. Novaes

We propose Markov two-components processes (M2CP) as a probabilistic model of asynchronous systems based on the trace semantics for concurrency. Considering an asynchronous system distributed over two sites, we introduce concepts and tools…

Systems and Control · Computer Science 2015-07-01 Samy Abbes

Let M be a noncompact metric space in which every closed ball is compact, and let G be a semigroup of Lipschitz mappings of M. Denote by (Y_n)_{n\geq1} a sequence of independent G-valued, identically distributed random variables (r.v.'s),…

Probability · Mathematics 2016-09-07 Hubert Hennion , Loic Herve

We present new concentration of measure inequalities for Markov chains, generalising results for chains that are contracting in Wasserstein distance. These are particularly suited to establishing the cut-off phenomenon for suitable chains.…

Probability · Mathematics 2022-05-24 Andrew Barbour , Graham Brightwell , Malwina Luczak

Let $Q$ be a transition probability on a measurable space $E$, let $(X\_n)\_n$ be a Markov chain associated to $Q$, and let $\xi$ be a real-valued measurable function on $E$, and $S\_n = \sum\_{k=1}^{n} \xi(X\_k)$. Under functional…

Probability · Mathematics 2007-05-23 Loïc Hervé

We prove an invariance principle (functional central limit theorem) for a vector-valued additive functional of a Markov chain for almost every starting point with respect to an ergodic equilibrium distribution. The hypothesis is a moment…

Probability · Mathematics 2011-10-20 F. Rassoul-Agha , T. Seppalainen

This paper studies Hoeffding's inequality for Markov chains under the generalized concentrability condition defined via integral probability metric (IPM). The generalized concentrability condition establishes a framework that interpolates…

Machine Learning · Statistics 2023-10-06 Hao Chen , Abhishek Gupta , Yin Sun , Ness Shroff

We provide explicit expressions for the constants involved in the characterisation of ergodicity of sub-geometric Markov chains. The constants are determined in terms of those appearing in the assumed drift and one-step minorisation…

Probability · Mathematics 2014-03-18 Christophe Andrieu , Gersende Fort , Matti Vihola

The central limit theorem for Markov chains generated by iterated function systems consisting of orientation preserving homeomorphisms of the interval is proved. We study also ergodicity of such systems.

Dynamical Systems · Mathematics 2020-03-24 Klaudiusz Czudek , Tomasz Szarek

We obtain non-Gaussian limit laws for one-dimensional random walk in a random environment assuming that the environment is a function of a stationary Markov process. This is an extension of the work of Kesten, M. Kozlov and Spitzer for…

Probability · Mathematics 2007-05-23 Eddy Mayer-Wolf , Alexander Roitershtein , Ofer Zeitouni

We prove exponential decay of pair correlations for 1D stationary point processes when spacings satisfy a Markov condition, geometric ergodicity, and a condition on exponential moments. The conditions are phrased for stationary sequences of…

Probability · Mathematics 2026-05-22 Yoon Jun Chan , Markus Heydenreich , Sabine Jansen

We analyze the probability distributions of the quantum walks induced from Markov chains by Szegedy (2004). The first part of this paper is devoted to the quantum walks induced from finite state Markov chains. It is shown that the…

Quantum Physics · Physics 2017-12-19 Radhakrishnan Balu , Chaobin Liu , Salvador E. Venegas-Andraca

We propose a new approach for estimating the finite dimensional transition matrix of a Markov chain using a large number of independent sample paths observed at random times. The sample paths may be observed as few as two times, and the…

Methodology · Statistics 2025-05-20 Daphne Aurouet , Valentin Patilea

We study quasi-stationary distributions and quasi-limiting behavior of Markov chains in general reducible state spaces with absorption. We propose a set of assumptions dealing with particular situations where the state space can be…

Probability · Mathematics 2026-01-14 Nicolas Champagnat , Denis Villemonais

The switch chain is a well-known Markov chain for sampling directed graphs with a given degree sequence. While not ergodic in general, we show that it is ergodic for regular degree sequences. We then prove that the switch chain is rapidly…

Combinatorics · Mathematics 2011-10-17 Catherine Greenhill

Given an ergodic finite-state Markov chain, let M_{iw} denote the mean time from i to equilibrium, meaning the expected time, starting from i, to arrive at a state selected randomly according to the equilibrium measure w of the chain. John…

Probability · Mathematics 2009-09-16 Peter G. Doyle