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Many economic models feature monotone Markov dynamics on state spaces that may be noncompact. Establishing existence, uniqueness, and stability of stationary distributions in such settings has required a patchwork of sufficient conditions,…

Probability · Mathematics 2026-04-07 Takashi Kamihigashi , John Stachurski

We study the pointwise stabilizability of a discrete-time, time-homogeneous, and stationary Markovian jump linear system. By using measure theory, ergodic theory and a splitting theorem of state space we show in a relatively simple way that…

Probability · Mathematics 2013-09-02 Xiongping Dai , Yu Huang , Mingqing Xiao

We generalize the well-known Coupon Collector Problem (CCP) in combinatorics. Our problem is to find the minimum and expected number of draws, with replacement, required to recover $n$ distinctly labeled coupons, with each draw consisting…

Discrete Mathematics · Computer Science 2025-07-22 Andrew Tan , Oriel Limor , Daniella Bar-Lev , Ryan Gabrys , Zohar Yakhini , Paul H. Siegel

We consider a Markov process $ X(t) $ on the nonnegative integers $E= S \cup \{0\}$, where $S=\{1,2,...\}$ is an irreducible class and 0 is an absorbing state. In this paper, we investigate conditions under which the quasi-stationary…

Probability · Mathematics 2014-10-09 Hanjun Zhang , Pengwen Guo , Yixia Zhu

We consider a vector of $N$ independent binary variables, each with a different probability of success. The distribution of the vector conditional on its sum is known as the conditional Bernoulli distribution. Assuming that $N$ goes to…

Computation · Statistics 2020-12-08 Jeremy Heng , Pierre E. Jacob , Nianqiao Ju

This paper is concerned with the solution of the optimal stopping problem associated to the valuation of Perpetual American options driven by continuous time Markov chains. We introduce a new dynamic approach for the numerical pricing of…

Probability · Mathematics 2019-04-25 Laurent Miclo , Stéphane Villeneuve

Let $V$ be an $n$-set, and let $X$ be a random variable taking values in the powerset of $V$. Suppose we are given a sequence of random coupons $X_1, X_2, \ldots $, where the $X_i$ are independent random variables with distribution given by…

Probability · Mathematics 2016-01-19 Victor Falgas-Ravry , Joel Larsson , Klas Markström

The configuration model is a standard tool for uniformly generating random graphs with a specified degree sequence, and is often used as a null model to evaluate how much of an observed network's structure can be explained by its degree…

Social and Information Networks · Computer Science 2023-05-31 Upasana Dutta , Bailey K. Fosdick , Aaron Clauset

The method of 'coupling from the past' permits exact sampling from the invariant distribution of a Markov chain on a finite state space. The coupling is successful whenever the stochastic dynamics are such that there is coalescence of all…

Probability · Mathematics 2025-10-17 Geoffrey R. Grimmett , Mark Holmes

Let $(X_n \colon n\in\Z)$ be a two-sided recurrent Markov chain with fixed initial state $X_0$ and let $\nu$ be a probability measure on its state space. We give a necessary and sufficient criterion for the existence of a non-randomized…

Probability · Mathematics 2015-06-11 Peter Morters , Istvan Redl

The paper analyzes the performance of tandem network of polling queue with setups. For a system with two-products and two-stations, we propose a new approach based on a partially-collapsible state-space characterization to reduce…

Performance · Computer Science 2022-02-22 Ravi Suman , Ananth Krishnamurthy

In this paper we study the central limit theorem for additive functionals of stationary Markov chains with general state space by using a new idea involving conditioning with respect to both the past and future of the chain. Practically, we…

Probability · Mathematics 2020-05-19 Magda Peligrad

Simple random coverage models, well studied in Euclidean space, can also be defined on a general compact metric space. By analogy with the geometric models, and with the discrete coupon collector's problem and with cover times for finite…

Probability · Mathematics 2021-02-01 David J. Aldous

Applications of stochastic models often involve the evaluation of steady-state performance, which requires solving a set of balance equations. In most cases of interest, the number of equations is infinite or even uncountable. As a result,…

Optimization and Control · Mathematics 2022-04-08 Shukai Li , Sanjay Mehrotra

We study the problem of learning the transition matrices of a set of Markov chains from a single stream of observations on each chain. We assume that the Markov chains are ergodic but otherwise unknown. The learner can sample Markov chains…

Machine Learning · Computer Science 2019-11-14 Mohammad Sadegh Talebi , Odalric-Ambrym Maillard

Understanding and predicting how complex systems respond to external perturbations is a central challenge in nonequilibrium statistical physics. Here we consider continuous-time Markov networks, which we subject to perturbations along a…

Statistical Mechanics · Physics 2026-02-25 Robin Bebon , Thomas Speck

For a discrete time Markov chain and in line with Strotz' consistent planning we develop a framework for problems of optimal stopping that are time-inconsistent due to the consideration of a non-linear function of an expected reward. We…

Optimization and Control · Mathematics 2020-01-23 Sören Christensen , Kristoffer Lindensjö

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

Sufficient conditions are provided under which the log-likelihood ratio test statistic fails to have a limiting chi-squared distribution under the null hypothesis when testing between one and two components under a general two-component…

Statistics Theory · Mathematics 2021-11-25 Matthew Fitzpatrick , Michael I. Stewart

We study convergence to equilibrium for a large class of Markov chains in random environment. The chains are sparse in the sense that in every row of the transition matrix $P$ the mass is essentially concentrated on few entries. Moreover,…

Probability · Mathematics 2018-01-23 Charles Bordenave , Pietro Caputo , Justin Salez