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The classical embeddability problem asks whether a given stochastic matrix $T$, describing transition probabilities of a $d$-level system, can arise from the underlying homogeneous continuous-time Markov process. Here, we investigate the…

We develop a central limit theorem (CLT) for a non-parametric estimator of the transition matrices in controlled Markov chains (CMCs) with finite state-action spaces. Our results establish precise conditions on the logging policy under…

Statistics Theory · Mathematics 2026-03-26 Ziwei Su , Imon Banerjee , Diego Klabjan

We are concerned with the absolute continuity of stationary distributions corresponding to some piecewise deterministic Markov process, being typically encountered in biological models. The process under investigation involves a…

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

This paper is devoted to studying the average optimality in continuous-time Markov decision processes with fairly general state and action spaces. The criterion to be maximized is expected average rewards. The transition rates of underlying…

Probability · Mathematics 2007-05-23 Xianping Guo , Ulrich Rieder

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

We extend in two directions our previous results about the sampling and the empirical measures of immortal branching Markov processes. Direct applications to molecular biology are rigorous estimates of the mutation rates of polymerase chain…

Probability · Mathematics 2007-05-23 Didier Piau

In the paper we consider some piecewise deterministic Markov process whose continuous component evolves according to semiflows, which are switched at the jump times of a Poisson process. The associated Markov chain describes the states of…

Probability · Mathematics 2023-10-06 Dawid Czapla , Sander C. Hille , Katarzyna Horbacz , Hanna Wojewódka-Ściążko

This paper introduces the concept of random context representations for the transition probabilities of a finite-alphabet stochastic process. Processes with these representations generalize context tree processes (a.k.a. variable length…

Probability · Mathematics 2016-12-09 Roberto Imbuzeiro Oliveira

We study the existence of densities for distributions of piecewise deterministic Markov processes. We also obtain relationships between invariant densities of the continuous time process and that of the process observed at jump times. In…

Probability · Mathematics 2020-06-03 Piotr Gwiżdż , Marta Tyran-Kamińska

We consider the fluctuations of a time-integrated particle current around an atypical value in a generic stochastic Markov process involving classical particles with two-site interaction and hardcore repulsion on a finite one-dimensional…

Statistical Mechanics · Physics 2016-01-20 Pegah Torkaman , Farhad H. Jafarpour

For a stochastically monotone Markov chain taking values in a Polish space, we present a number of conditions for existence and for uniqueness of its stationary regime, as well as for closeness of its transient trajectories. In particular,…

Probability · Mathematics 2026-04-02 Sergey Foss , Michael Scheutzow

Stochastic kinetic models (SKMs) are increasingly used to account for the inherent stochasticity exhibited by interacting populations of species in areas such as epidemiology, population ecology and systems biology. Species numbers are…

Computation · Statistics 2023-04-06 Tom E. Lowe , Andrew Golightly , Chris Sherlock

This paper is concerned with the development of rigorous approximations to various expectations associated with Markov chains and processes having non-stationary transition probabilities. Such non-stationary models arise naturally in…

Probability · Mathematics 2018-05-07 Zeyu Zheng , Harsha Honnappa , Peter W. Glynn

Piecewise-deterministic Markov processes (PDMPs) offer a powerful stochastic modeling framework that combines deterministic trajectories with random perturbations at random times. Estimating their local characteristics (particularly the…

Methodology · Statistics 2025-12-29 Romain Azaïs , Solune Denis

We propose a method based on continuous time Markov chain approximation to compute the distribution of Parisian stopping times and price Parisian options under general one-dimensional Markov processes. We prove the convergence of the method…

Computational Finance · Quantitative Finance 2021-07-15 Gongqiu Zhang , Lingfei Li

Stochastic birth-death processes are described as continuous-time Markov processes in models of population dynamics. A system of infinite, coupled ordinary differential equations (the so-called master equation) describes the time-dependence…

Mathematical Physics · Physics 2019-01-21 Primitivo B. Acosta-Humanez , Jose A. Capitan , Juan J. Morales-Ruiz

To determine the effect of nonradiative excitation energy transfer on the fluorescence of a rigid multicomponent solution, a new analytical method was developed by treating this transfer as a time-resolved Markov chain (TRMC). In the TRMC…

Chemical Physics · Physics 2025-09-16 Józef Kuśba

We consider a stochastic spatial point process with births and deaths on $\mathbb{R}^d$, with the hard-core property that at any time the balls of radius half of any two points do not overlap. We give explicit construction of the process.…

Probability · Mathematics 2016-04-19 Mayank Manjrekar

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

This article aims to investigate sufficient conditions for the stability of stochastic differential equations with a random structure, particularly in contexts involving the presence of concentration points. The proof of asymptotic…

Probability · Mathematics 2023-05-22 Taras Lukashiv , Igor V. Malyk , Maryna Chepeleva , Petr V. Nazarov
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