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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

In this note, a general approach to the study of non-stationary Markov chains with catastrophes and the corresponding queuing models is considered, as well as to obtain estimates of the limiting regime itself. As an illustration, an example…

Probability · Mathematics 2021-05-05 Alexander Zeifman

Questions are posed regarding the influence that the column sums of the transition probabilities of a stochastic matrix (with row sums all one) have on the stationary distribution, the mean first passage times and the Kemeny constant of the…

Probability · Mathematics 2014-03-05 Jeffrey J. Hunter

In this paper, we study quasi-stationary distributions of nonlinearly perturbed semi-Markov processes in discrete time. This type of distributions is of interest for the analysis of stochastic systems which have finite lifetimes, but are…

Probability · Mathematics 2016-04-28 Mikael Petersson

We establish sufficient conditions for exponential convergence to a unique quasi-stationary distribution in the total variation norm. These conditions also ensure the existence and exponential ergodicity of the Q-process, the process…

Probability · Mathematics 2023-08-01 Aurélien Velleret

For the continuous-time $\lambda$-recurrent jump process, the $\lambda$-recurrence assures the existence of quasi-stationary distribution when it has finite exit states (the states that have positive killing rates). And we give an explicit…

Probability · Mathematics 2024-07-30 Qian Du , Yong-Hua Mao

We study the long time behaviour of a Markov process evolving in $\mathbb{N}$ and conditioned not to hit 0. Assuming that the process comes back quickly from infinity, we prove that the process admits a unique quasi-stationary distribution…

Probability · Mathematics 2013-04-04 Servet Martinez , Jaime San Martin , Denis Villemonais

There is a well-established theory linking certain semi-Markov chains and continuous-time random walks to time-fractional equations and anomalous diffusion. In this work, we go beyond the semi-Markov framework by considering some…

Probability · Mathematics 2026-02-27 Lorenzo Facciaroni , Costantino Ricciuti , Enrico Scalas

In this work, we focus on the stationary analysis of a specific class of continuous time Markov-modulated reflected random walks in the quarter plane with applications in the modelling of two-node Markov-modulated queueing networks with…

Probability · Mathematics 2020-06-02 Ioannis Dimitriou

We are interested in quasi-stationarity and quasi-ergodicity when the absorbing boundary is moving. First we show that, in the moving boundary case, the quasi-stationary distribution and the quasi-limiting distribution are not well-defined…

Probability · Mathematics 2019-11-25 William Oçafrain

Let $(X,\p_x)$ be a continuous time Markov chain with finite or countable state space $S$ and let $T$ be its first passage time in a subset $D$ of $S$. It is well known that if $\mu$ is a quasi-stationary distribution relatively to $T$,…

Probability · Mathematics 2013-10-25 Romain Bourget , Loïc Chaumont , Natalia Sapoukhina

In the setting of stochastic dynamical systems that eventually go extinct, the quasi-stationary distributions are useful to understand the long-term behavior of a system before evanescence. For a broad class of applicable continuous-time…

Probability · Mathematics 2018-08-22 Mads Christian Hansen , Carsten Wiuf

Let $X_n, n \ge 0$ be a Markov chain with finite state space $M$. If $x,y \in M$ such that $x$ is transient we have $P^y(X_n = x) \to 0$ for $n \to \infty$, and under mild aperiodicity conditions this convergence is monotone in that for…

Probability · Mathematics 2025-03-25 Philipp König , Thomas Richthammer

For downward skip-free continuous-time Markov chains on non-negative integers stopped at zero, existence of a quasi-stationary distribution is studied. The scale function for these processes is introduced and the boundary is classified by a…

Probability · Mathematics 2023-03-03 Kosuke Yamato

For general, almost surely absorbed Markov processes, we obtain necessary and sufficient conditions for exponential convergence to a unique quasi-stationary distribution in the total variation norm. These conditions also ensure the…

Probability · Mathematics 2014-12-25 Nicolas Champagnat , Denis Villemonais

We consider a stationary Markov process that models certain queues with a bulk service of a fixed number $m$ of admitted customers. We find an integral expression of its transition probability function in terms of certain multi-orthogonal…

Probability · Mathematics 2023-08-29 Ulises Fidalgo

In this brief note, we find formulas for the distribution and the transition probability matrices of a stochastic process described as a time-reversion in a finite time window of a Markov chain, with cluster observation of the Markov state…

Probability · Mathematics 2022-06-14 Daniel A. Gutierrez-Pachas , Eduardo F. Costa , Alessandro N. Vargas

Consider longitudinal networks whose edges turn on and off according to a discrete-time Markov chain with exponential-family transition probabilities. We characterize when their joint distributions are also exponential families with the…

Methodology · Statistics 2024-03-12 William K. Schwartz , Sonja Petrović , Hemanshu Kaul

We consider Markov chains on partially ordered sets that generalize the success-runs and remaining life chains in reliability theory. We find conditions for recurrence and transience and give simple expressions for the invariant…

Probability · Mathematics 2010-04-08 Kyle Siegrist

For Markov processes with absorption, we provide general criteria ensuring the existence and the exponential non-uniform convergence in total variation norm to a quasi-stationary distribution. We also characterize a subset of its domain of…

Probability · Mathematics 2022-10-24 Nicolas Champagnat , Denis Villemonais
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