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Stochastically monotone Markov chains arise in many applied domains, especially in the setting of queues and storage systems. Poisson's equation is a key tool for analyzing additive functionals of such models, such as cumulative sums of…

Probability · Mathematics 2022-02-23 Peter W. Glynn , Alex Infanger

In this paper we give explicit examples of power-law correlated stationary Markovian processes y(t) where the stationary pdf shows tails which are gaussian or exponential. These processes are obtained by simply performing a coordinate…

Statistical Mechanics · Physics 2010-12-08 Salvatore Miccichè

Stochastic models of biochemical reaction networks are widely used to capture intrinsic noise in cellular systems. The typical formulation of these models are based on Markov processes for which there is extensive research on efficient…

Molecular Networks · Quantitative Biology 2025-12-03 Thomas P. Steele , David J. Warne

Epigenetic cell memory, the inheritance of gene expression patterns across subsequent cell divisions, is a critical property of multi-cellular organisms. In recent work [10], a subset of the authors observed in a simulation study how the…

Probability · Mathematics 2024-05-17 Simone Bruno , Felipe A. Campos , Yi Fu , Domitilla Del Vecchio , Ruth J. Williams

This report proposes a novel framework for a rigorous robustness analysis of stochastic biochemical systems. The technique is based on probabilistic model checking. We adapt the general definition of robustness introduced by Kitano to the…

Numerical Analysis · Computer Science 2013-10-18 Lubos Brim , Milan Ceska , Sven Drazan , David Safranek

Physical parameterizations are used as representations of unresolved subgrid processes within weather and global climate models or coarse-scale turbulent models, whose resolutions are too coarse to resolve small-scale processes. These…

Machine Learning · Statistics 2022-10-27 Mohamed Aziz Bhouri , Pierre Gentine

Renewal theorems are developed for point processes with interarrival times $W_n=\xi(X_{n+1}X_n\cdots)$, where $(X_n)_{n\in\mathbb Z}$ is a stochastic process with finite state space $\Sigma$ and $\xi\colon\Sigma_A\to\mathbb R$ is a H\"older…

Probability · Mathematics 2023-02-09 Sabrina Kombrink

We present a short introduction into the framework of piecewise deterministic Markov processes. We illustrate the abstract mathematical setting with a series of examples related to dispersal of biological systems, cell cycle models, gene…

Probability · Mathematics 2015-12-08 Ryszard Rudnicki , Marta Tyran-Kaminska

A novel class of non-reversible Markov chain Monte Carlo schemes relying on continuous-time piecewise-deterministic Markov Processes has recently emerged. In these algorithms, the state of the Markov process evolves according to a…

Methodology · Statistics 2018-05-16 Paul Vanetti , Alexandre Bouchard-Côté , George Deligiannidis , Arnaud Doucet

Poisson restart assumes that a stochastic process is interrupted and starts again at random time moments. A number of studies have demonstrated that this strategy may minimize the expected completion time in some classes of random search…

Statistical Mechanics · Physics 2024-05-15 Sergey Belan

The paper deals with a certain class of random evolutions. We develop a construction that yields an invariant measure for a continuous-time Markov process with random transitions. The approach is based on a particular way of constructing…

Probability · Mathematics 2015-10-20 Y. Belopolskaya , Y. Suhov

We analyze a class of spatial random spanning trees built on a realization of a homogeneous Poisson point process of the plane. This tree has a simple radial structure with the origin as its root. We first use stochastic geometry arguments…

Probability · Mathematics 2007-05-23 Francois Baccelli , Charles Bordenave

Case-Bsed Reasoning (CBR) is a recent theory for problem-solving and learning in computers and people.Broadly construed it is the process of solving new problems based on the solution of similar past problems. In the present paper we…

Artificial Intelligence · Computer Science 2014-01-07 Michael Gr. Voskoglou

We revisit processes generated by iterated random functions driven by a stationary and ergodic sequence. Such a process is called strongly stable if a random initialization exists, for which the process is stationary and ergodic, and for…

Probability · Mathematics 2024-02-06 László Györfi , Attila Lovas , Miklós Rásonyi

Finite stochastic Markov models play a major role for modelling biochemical pathways. Such models are a coarse-grained description of the underlying microscopic dynamics and can be considered mesoscopic. The level of coarse-graining is to a…

Biological Physics · Physics 2012-06-05 Bernhard Altaner , Jürgen Vollmer

We construct a Markov process model to describe the evolution of labor division and its dynamical behavior is investigated by numerical simulations in detail. We have shown that under the mechanism of increasing returns, the division of…

Adaptation and Self-Organizing Systems · Physics 2007-05-23 Lei Chai , Dahui Wang , Jiawei Chen , Zengru Di

Poisson's equation plays a fundamental role as a tool for performance evaluation and optimization of Markov chains. For continuous-time birth-death chains with possibly unbounded transition and cost rates as addressed herein, when…

Probability · Mathematics 2022-07-28 José Niño-Mora

In this paper, we propose a novel stochastic process that serves as a natural discrete-time counterpart to the continuous-time model known as the ``Poisson hyperbolic staircase'' proposed by Levikson et al. (1999), and clarify its…

Probability · Mathematics 2026-04-27 Naohiro Yoshida

The ordinary contact process is used to model the spread of a disease in a population. In this model, each infected individual waits an exponentially distributed time with parameter 1 before becoming healthy. In this paper, we introduce and…

Probability · Mathematics 2011-11-10 Erik I. Broman

We study the tail behavior of Markov-modulated generalized Ornstein-Uhlenbeck processes -- that is, solutions to Langevin-type stochastic differential equations driven by a background continuous-time Markov chain. To this end, we consider a…

Probability · Mathematics 2026-01-15 Gerold Alsmeyer , Anita Behme