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We consider continuous-time Markov chain on a finite state space X. We assume X can be clustered into several subsets such that the intra-transition rates within these subsets are of order $\mathcal{O}(\frac{1}{\epsilon})$ comparing to the…

Probability · Mathematics 2016-01-28 Wei Zhang

We consider the convergence of a continuous-time Markov chain approximation X^h, h>0, to an R^d-valued Levy process X. The state space of X^h is an equidistant lattice and its Q-matrix is chosen to approximate the generator of X. In…

Probability · Mathematics 2014-07-02 Aleksandar Mijatović , Matija Vidmar , Saul Jacka

A stable-like Markov chain is a time-homogeneous Markov chain on the real line with the transition kernel $p(x,dy)=f_x(y-x)dy$, where the density functions $f_x(y)$, for large $|y|$, have a power-law decay with exponent $\alpha(x)+1$, where…

Probability · Mathematics 2014-12-01 Nikola Sandrić

We consider continuous-time Markov chains on integers which allow transitions to adjacent states only, with alternating rates. We give explicit formulas for probability generating functions, and also for means, variances and state…

Probability · Mathematics 2019-10-30 Luisa Beghin , Claudio Macci , Barbara Martinucci

We provide a coupling proof of Doob's theorem which says that the transition probabilities of a regular Markov process which has an invariant probability measure $\mu$ converge to $\mu$ in the total variation distance. In addition we show…

Probability · Mathematics 2014-08-01 Alexei Kulik , Michael Scheutzow

In this paper, we consider semi-Markov processes whose transition times and transition probabilities depend on a small parameter $\varepsilon$. Understanding the asymptotic behavior of such processes is needed in order to study the…

Probability · Mathematics 2024-11-08 Leonid Koralov , Ishfaaq Mohammed Imtiyas

Let us consider a homogeneous Markov chain with discrete time and with a finite set of states $E_0,\ldots,E_n$ such that the state $E_0$ is absorbing, states $E_1,\ldots,E_n$ are nonrecurrent. The goal of this work is to study frequencies…

Information Theory · Computer Science 2013-08-23 Vladimir V. Bochkarev , Eduard Yu. Lerner

Suppose that $(X_t)_{t \ge 0}$ is a one-dimensional Brownian motion with negative drift $-\mu$. It is possible to make sense of conditioning this process to be in the state $0$ at an independent exponential random time and if we kill the…

Probability · Mathematics 2019-08-28 Steven N. Evans , Alexandru Hening

We prove several necessary and sufficient conditions for the existence of (smooth) transition probability densities for L\'evy processes and isotropic L\'evy processes. Under some mild conditions on the characteristic exponent we calculate…

Probability · Mathematics 2014-07-31 V. Knopova , R. L. Schilling

In this paper, we derive a simple drift condition for the stability of a class of two-dimensional Markov processes, for which one of the coordinates (also referred to as the {\em phase} for convenience) has a well understood behaviour…

Probability · Mathematics 2020-10-01 Stella Kapodistria , Seva Shneer

We consider the problem of conditioning a Markov process on a rare event and of representing this conditioned process by a conditioning-free process, called the effective or driven process. The basic assumption is that the rare event used…

Statistical Mechanics · Physics 2015-08-17 Raphael Chetrite , Hugo Touchette

Doob fixed-time conditioning enables the sampling of rare trajectories of Markov processes by modifying the drift so that reaching a prescribed target at a given time is guaranteed. We study the statistics of this conditioned path ensemble…

Statistical Mechanics · Physics 2026-05-26 Iago N. Mamede , Francesco Coghi

We establish non-asymptotic error bounds for the classical Maximal Likelihood Estimation of the transition matrix of a given Markov chain. Meanwhile, in the reversible case, we propose a new reversibility-preserving online Symmetric…

Statistics Theory · Mathematics 2025-11-07 De Huang , Xiangyuan Li

We are interested in the asymptotic behavior of Markov chains on the set of positive integers for which, loosely speaking, large jumps are rare and occur at a rate that behaves like a negative power of the current state, and such that small…

Probability · Mathematics 2018-02-19 Jean Bertoin , Igor Kortchemski

Markov branching systems form a fundamental class of stochastic models that are extensively applied in biology, physics, finance, and other domains. These systems are distinguished by their continuous-time evolution and inherent branching…

The asymptotic normality in multi-dimension of the nonparametric estimator of the transition probabilities of a Markov renewal chain is proved, and is applied to that of other nonparametric estimators involved with the associated…

Statistics Theory · Mathematics 2023-04-11 Hiroki Ogata , Luis Iván Hernández Ruíz , Kouji Yano

The spectral gap $\gamma$ of a finite, ergodic, and reversible Markov chain is an important parameter measuring the asymptotic rate of convergence. In applications, the transition matrix $P$ may be unknown, yet one sample of the chain up to…

Statistics Theory · Mathematics 2017-08-25 Daniel Hsu , Aryeh Kontorovich , David A. Levin , Yuval Peres , Csaba Szepesvári

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

We consider a discrete time semi-Markov process where the characteristics defining the process depend on a small perturbation parameter. It is assumed that the state space consists of one finite communicating class of states and, in…

Probability · Mathematics 2016-03-21 Mikael Petersson

We give conditions under which near-critical stochastic processes on the half-line have infinitely many or finitely many cutpoints, generalizing existing results on nearest-neighbour random walks to adapted processes with bounded increments…

Probability · Mathematics 2022-03-21 Chak Hei Lo , Mikhail V. Menshikov , Andrew R. Wade