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We prove that moderate deviations for empirical measures for countable nonhomogeneous Markov chains hold under the assumption of uniform convergence of transition probability matrices for countable nonhomogeneous Markov chains in Ces\`aro…

Probability · Mathematics 2020-10-16 Mingzhou Xu , Kun Cheng

In this paper we are concerned with hitting times of a family of density-dependent Markov chains. A moderate deviation principle of the hitting time is given. The proof of the main theorem relies heavily on moderate deviations of…

Probability · Mathematics 2022-06-15 Yuheng He , Xiaofeng Xue

A new approach to computation of optimal policies for MDP (Markov decision process) models is introduced. The main idea is to solve not one, but an entire family of MDPs, parameterized by a weighting factor $\zeta$ that appears in the…

Optimization and Control · Mathematics 2018-09-18 Ana Bušić , Sean Meyn

We study the limit behaviour of a generally non-linear ordinary differential equation whose solution is a superadditive generalisation of a stochastic matrix, and provide necessary and sufficient conditions for this solution to be ergodic,…

Probability · Mathematics 2016-09-21 Jasper De Bock

We extend Hoeffding's lemma to general-state-space and not necessarily reversible Markov chains. Let $\{X_i\}_{i \ge 1}$ be a stationary Markov chain with invariant measure $\pi$ and absolute spectral gap $1-\lambda$, where $\lambda$ is…

Statistics Theory · Mathematics 2018-07-19 Jianqing Fan , Bai Jiang , Qiang Sun

In this paper, we derive the moderate deviation principle for stationary sequences of bounded random variables with values in a Hilbert space. The conditions obtained are expressed in terms of martingale-type conditions. The main tools are…

Probability · Mathematics 2009-01-21 Sophie Dede

Let $X:=(X_t)_{t\geq 0}$ be an ergodic Markov process on $\real^d$, and $p>0$. We derive upper bounds of the $p$-Wasserstein distance between the invariant measure and the empirical measures of the Markov process $X$. For this we assume,…

Probability · Mathematics 2025-12-30 René L. Schilling , Jian Wang , Bingyao Wu , Jie-Xiang Zhu

We establish a new Bernstein-type deviation inequality for general (non-reversible) discrete-time Markov chains via an elementary approach. More robust than existing works in the literature, our result only requires the Markov chain to…

Probability · Mathematics 2025-10-07 De Huang , Xiangyuan Li

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

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

Let $A_N$ be distributed according to the Haar probability measure on the orthogonal group $\mathscr{O}(N)$ for each $N\in\mathbb{N}$. It is well-known that the upper left $m_N\times k_N$ block of $\sqrt{N}A_N$ with $m_Nk_N = o(N)$…

Probability · Mathematics 2025-09-30 Philipp Tuchel

This paper studies the subgeometric convergence of the stationary distribution in taking the infinite-level limit of a finite-level M/G/1-type Markov chain, that is, in letting the upper boundary level go to infinity. This study is…

Probability · Mathematics 2022-09-07 Hiroyuki Masuyama , Yosuke Katsumata , Tatsuaki Kimura

Our purpose is to prove central limit theorem for countable nonhomogeneous Markov chain under the condition of uniform convergence of transition probability matrices for countable nonhomogeneous Markov chain in Ces\`aro sense. Furthermore,…

Probability · Mathematics 2020-10-15 Mingzhou Xu , Yunzheng Ding , Yongzheng Zhou

We consider the irreducibility of switch-based Markov chains for the approximate uniform sampling of Hamiltonian cycles in a given undirected dense graph on $n$ vertices. As our main result, we show that every pair of Hamiltonian cycles in…

Combinatorics · Mathematics 2020-11-20 Pieter Kleer , Viresh Patel , Fabian Stroh

In Markov Decision Processes (MDPs) with intermittent state information, decision-making becomes challenging due to periods of missing observations. Linear programming (LP) methods can play a crucial role in solving MDPs, in particular,…

Optimization and Control · Mathematics 2025-09-09 Konstantin Avrachenkov , Madhu Dhiman , Veeraruna Kavitha

We consider the problem of statistical inference in a parametric finite Markov chain model and develop a robust estimator of the parameters defining the transition probabilities via minimization of a suitable (empirical) version of the…

Methodology · Statistics 2021-03-23 Abhik Ghosh

The spectral gap of a Markov chain can be bounded by the spectral gaps of constituent "restriction" chains and a "projection" chain, and the strength of such a bound is the content of various decomposition theorems. In this paper, we…

Data Structures and Algorithms · Computer Science 2019-10-14 Sarah Miracle , Amanda Pascoe Streib , Noah Streib

We consider periodic Markov chains with absorption. Applying to iterates of this periodic Markov chain criteria for the exponential convergence of conditional distributions of aperiodic absorbed Markov chains, we obtain exponential…

Probability · Mathematics 2022-11-08 Nicolas Champagnat , Denis Villemonais

A family $\{Q_{\beta}\}_{\beta \geq 0}$ of Markov chains is said to exhibit $\textit{metastable mixing}$ with $\textit{modes}$ $S_{\beta}^{(1)},\ldots,S_{\beta}^{(k)}$ if its spectral gap (or some other mixing property) is very close to the…

Probability · Mathematics 2021-07-01 Oren Mangoubi , Natesh S. Pillai , Aaron Smith

We analyse the $\ell^2(\pi)$-convergence rate of irreducible and aperiodic Markov chains with $N$-band transition probability matrix $P$ and with invariant distribution $\pi$. This analysis is heavily based on: first the study of the…

Probability · Mathematics 2016-01-15 Loïc Hervé , James Ledoux