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Consider a compact metric space $S$ and a pair $(j,k)$ with $k \ge 2$ and $1 \le j \le k$. For any probability distribution $\theta \in P(S)$, define a Markov chain on $S$ by: from state $s$, take $k$ i.i.d. ($\theta$) samples, and jump to…

Probability · Mathematics 2024-04-03 David J. Aldous , Shi Feng

This is an expository review paper illustrating the ``martingale method'' for proving many-server heavy-traffic stochastic-process limits for queueing models, supporting diffusion-process approximations. Careful treatment is given to an…

Probability · Mathematics 2007-12-28 Guodong Pang , Rishi Talreja , Ward Whitt

We study an $n$-species $t$-PushTASEP, an integrable long-range stochastic process, on a one-dimensional periodic lattice with inhomogeneities $x_1,\ldots,x_L$ and arbitrary capacity $l$ at each lattice site. The Markov matrix is identified…

Mathematical Physics · Physics 2026-02-20 Arvind Ayyer , Atsuo Kuniba

We study a Markov chain on $\mathbb{R}_+ \times S$, where $\mathbb{R}_+$ is the non-negative real numbers and $S$ is a finite set, in which when the $\mathbb{R}_+$-coordinate is large, the $S$-coordinate of the process is approximately…

Probability · Mathematics 2017-04-14 Chak Hei Lo , Andrew R. Wade

We consider moments of the return times (or first hitting times) in a discrete time discrete space Markov chain. It is classical that the finiteness of the first moment of a return time of one state implies the finiteness of the first…

Probability · Mathematics 2012-09-03 Frank Aurzada , Hanna Doering , Marcel Ortgiese , Michael Scheutzow

The probability that a max-stable process {\eta} in C[0, 1] with identical marginal distribution function F hits x \in R with 0 < F (x) < 1 is the hitting probability of x. We show that the hitting probability is always positive, unless the…

Probability · Mathematics 2012-06-27 Martin Hofmann

Recursive stochastic algorithms have gained significant attention in the recent past due to data driven applications. Examples include stochastic gradient descent for solving large-scale optimization problems and empirical dynamic…

Machine Learning · Computer Science 2020-07-27 Abhishek Gupta , Hao Chen , Jianzong Pi , Gaurav Tendolkar

We consider a class of stochastic dynamical systems, called piecewise deterministic Markov processes, with states $(x, \s)\in \O\times \G$, $\O$ being a region in $\bbR^d$ or the $d$--dimensional torus, $\G$ being a finite set. The…

Statistical Mechanics · Physics 2009-02-25 Alessandra Faggionato , Davide Gabrielli , Marco Ribezzi Crivellari

In this paper, we study a subclass of piecewise-deterministic Markov processes with a Polish state space, involving deterministic motion punctuated by random jumps that occur at exponentially distributed time intervals. Over each of these…

Probability · Mathematics 2024-03-26 Dawid Czapla , Katarzyna Horbacz , Hanna Wojewódka-Ściążko

In this article, we consider additive functionals $\zeta_t = \int_0^t f(X_s)\mathrm{d} s$ of a c\`adl\`ag Markov process $(X_t)_{t\geq 0}$ on $\mathbb{R}$. Under some general conditions on the process $(X_t)_{t\geq 0}$ and on the function…

Probability · Mathematics 2023-04-19 Quentin Berger , Loïc Béthencourt , Camille Tardif

We consider the problem of sampling from a log-concave distribution $\pi(\theta) \propto e^{-f(\theta)}$ constrained to a polytope $K:=\{\theta \in \mathbb{R}^d: A\theta \leq b\}$, where $A\in \mathbb{R}^{m\times d}$ and $b \in…

Data Structures and Algorithms · Computer Science 2024-09-09 Oren Mangoubi , Nisheeth K. Vishnoi

We study a continuous time Markov process whose state space consists of an assignment of +1 or -1 to each vertex of a graph G. The graphs that we treat are related to homogeneous trees of degree K $\geq$ 3, such as finite or infinite stacks…

Probability · Mathematics 2015-03-24 Sinziana M. Eckner , Charles M. Newman

We study the convergence of random function iterations for finding an invariant measure of the corresponding Markov operator. We call the problem of finding such an invariant measure the stochastic fixed point problem. This generalizes…

Optimization and Control · Mathematics 2024-04-16 Neal Hermer , D. Russell Luke , Anja Sturm

A Markov Additive Process is a bi-variate Markov process $(\xi,J)=\big((\xi_t,J_t),t\geq0\big)$ which should be thought of as a multi-type L\'evy process: the second component $J$ is a Markov chain on a finite space $\{1,\ldots,K\}$, and…

Probability · Mathematics 2018-10-04 Robin Stephenson

We investigate a piecewise-deterministic Markov process, evolving on a Polish metric space, whose deterministic behaviour between random jumps is governed by some semi-flow, and any state right after the jump is attained by a randomly…

Probability · Mathematics 2020-12-04 Dawid Czapla , Sander C. Hille , Katarzyna Horbacz , Hanna Wojewódka-Ściążko

We study asymptotic properties of the following Markov system of $N \geq 3$ points in~$[0,1]$. At each time step, the point farthest from the current centre of mass, multiplied by a constant $p>0$, is removed and replaced by an independent…

Probability · Mathematics 2019-11-20 Philip Kennerberg , Stanislav Volkov

For near-critical, transient Markov chains on the non-negative integers in the Lamperti regime, where the mean drift at $x$ decays as $1/x$ as $x \to \infty$, we quantify degree of transience via existence of moments for conditional return…

Probability · Mathematics 2024-05-07 Chak Hei Lo , Mikhail V. Menshikov , Andrew R. Wade

In this paper, we establish a version of the central limit theorem for Markov-Feller continuous time processes (with a Polish state space) that are exponentially ergodic in the bounded-Lipschitz distance and enjoy a continuous form of the…

Probability · Mathematics 2023-10-09 Dawid Czapla , Katarzyna Horbacz , Hanna Wojewódka-Ściążko

Given a sequence of i.i.d. random functions $\Psi_{n}:\mathbb{R}\to\mathbb{R}$, $n\in\mathbb{N}$, we consider the iterated function system and Markov chain which is recursively defined by $X_{0}^{x}:=x$ and…

Probability · Mathematics 2021-10-07 Gerold Alsmeyer , Sara Brofferio , Dariusz Buraczewski

Continuous Time Markov Chains, Hawkes processes and many other interesting processes can be described as solution of stochastic differential equations driven by Poisson measures. Previous works, using the Stein's method, give the…

Probability · Mathematics 2026-04-02 Eustache Besançon , Laure Coutin , Laurent Decreusefond , Pascal Moyal
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