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We study the stochastic dynamics of coupled states with transition probabilities depending on local persistence, this is, the time since a state has changed. When the population has a preference to adopt older states the system orders…

Physics and Society · Physics 2016-03-22 Toni Pérez , Konstantin Klemm , Víctor M. Eguíluz

This paper presents a set of results relating to the occupation time $\alpha(t)$ of a process $X(\cdot)$. The first set of results concerns exact characterizations of $\alpha(t)$ for $t\geq0$, e.g., in terms of its transform up to an…

Probability · Mathematics 2018-09-03 N. J. Starreveld , R. Bekker , M. Mandjes

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

In the analysis of Markov chains and processes, it is sometimes convenient to replace an unbounded state space with a "truncated" bounded state space. When such a replacement is made, one often wants to know whether the equilibrium behavior…

Probability · Mathematics 2022-03-30 Alex Infanger , Peter W. Glynn , Yuanyuan Liu

We consider two types of discrete-time Markov chains where the state space is a graded poset and the transitions are taken along the covering relations in the poset. The first type of Markov chain goes only in one direction, either up or…

Probability · Mathematics 2016-08-06 Kimmo Eriksson , Markus Jonsson , Jonas Sjöstrand

In this paper, we establish moment and Bernstein-type inequalities for additive functionals of geometrically ergodic Markov chains. These inequalities extend the corresponding inequalities for independent random variables. Our conditions…

Probability · Mathematics 2023-06-16 Alain Durmus , Eric Moulines , Alexey Naumov , Sergey Samsonov

We investigate recurrence and transience of Branching Markov Chains (BMC) in discrete time. Branching Markov Chains are clouds of particles which move (according to an irreducible underlying Markov Chain) and produce offspring…

Probability · Mathematics 2016-09-07 Nina Gantert , Sebastian Mueller

We consider triangular arrays of Markov chains that converge weakly to a diffusion process. Local limit theorems for transition densities are proved. The observation time [0,T] may be fixed or lim n T = 0, where nh = T and h is a mesh…

Probability · Mathematics 2007-06-13 Valentin Konakov

We study an exactly solvable random walk model with long-range memory on arbitrary networks. The walker performs unbiased random steps to nearest-neighbor nodes and intermittently resets to previously visited nodes in a preferential way,…

Statistical Mechanics · Physics 2024-12-11 Ana Gabriela Guerrero-Estrada , Alejandro P. Riascos , Denis Boyer

Occupancy processes are a broad class of discrete time Markov chains on $\{0,1\}^{n}$ encompassing models from diverse areas. This model is compared to a collection of $n$ independent Markov chains on $\{0,1\}$, which we call the…

Probability · Mathematics 2025-12-09 Ross McVinish

Let $X_n$ be a discrete time Markov chain with state space $S$ (countably infinite, in general) and initial probability distribution $\mu^{(0)} = (P(X_0=i_1),P(X_0=i_2),\cdots,)$. What is the probability of choosing in random some $k \in…

Probability · Mathematics 2017-08-01 Nikolaos Halidias

We develop a model for credit rating migration that accounts for the impact of economic state fluctuations on default probabilities. The joint process for the economic state and the rating is modelled as a time-homogeneous Markov chain.…

Risk Management · Quantitative Finance 2024-03-25 Michael Kalkbrener , Natalie Packham

We consider a time-slotted job-assignment system with a central server, N users and a machine which changes its state according to a Markov chain (hence called a Markov machine). The users submit their jobs to the central server according…

Information Theory · Computer Science 2026-02-17 Stavros Mitrolaris , Subhankar Banerjee , Sennur Ulukus

We introduce the concept of a Markov influence system (MIS) and analyze its dynamics. An MIS models a random walk in a graph whose edges and transition probabilities change endogenously as a function of the current distribution. This…

Multiagent Systems · Computer Science 2019-03-28 Bernard Chazelle

We prove the existence of limiting distributions for a large class of Markov chains on a general state space in a random environment. We assume suitable versions of the standard drift and minorization conditions. In particular, the system…

Probability · Mathematics 2020-12-04 Attila Lovas , Miklós Rásonyi

We investigate the effects of markovian resseting events on continuous time random walks where the waiting times and the jump lengths are random variables distributed according to power law probability density functions. We prove the…

Statistical Mechanics · Physics 2021-02-10 Vicenç Méndez , Axel Masó-Puigdellosas , Trifce Sandev , Daniel Campos

We describe a Markov-Chain-Monte-Carlo algorithm which can be used to generate naturally labeled n-element posets at random with a probability distribution of one's choice. Implementing this algorithm for the uniform distribution, we…

Combinatorics · Mathematics 2015-04-23 Joe Henson , David P. Rideout , Rafael D. Sorkin , Sumati Surya

The focus of this article is on entropy and Markov processes. We study the properties of functionals which are invariant with respect to monotonic transformations and analyze two invariant "additivity" properties: (i) existence of a…

Data Analysis, Statistics and Probability · Physics 2013-11-12 A. N. Gorban , P. A. Gorban , G. Judge

In this article, we consider a Branching Random Walk on the real line. The genealogical structure is assumed to be given through a supercritical branching process in the i.i.d. environment and satisfies the Kesten-Stigum condition. The…

Probability · Mathematics 2023-02-02 Ayan Bhattacharya , Zbigniew Palmowski

We consider a simple but important class of metastable discrete time Markov chains, which we call perturbed Markov chains. Basically, we assume that the transition matrices depend on a parameter $\varepsilon$, and converge as $\varepsilon$.…

Probability · Mathematics 2014-12-23 Volker Betz , Stéphane Le Roux
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