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Scientific explanation often requires inferring maximally predictive features from a given data set. Unfortunately, the collection of minimal maximally predictive features for most stochastic processes is uncountably infinite. In such…

Statistical Mechanics · Physics 2017-05-31 Sarah E. Marzen , James P. Crutchfield

In this paper, we investigate the functional central limit theorem for stochastic processes associated to partial sums of additive functionals of reversible Markov chains with general spate space, under the normalization standard deviation…

Probability · Mathematics 2022-08-02 Magda Peligrad , Sergey Utev

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 study termination of higher-order probabilistic functional programs with recursion, stochastic conditioning and sampling from continuous distributions. Reasoning about the termination probability of programs with continuous distributions…

Programming Languages · Computer Science 2021-04-13 Raven Beutner , Luke Ong

We consider a Markov modulated fluid network with a finite number of stations. We are interested in the tail asymptotics behavior of the stationary distribution of its buffer content process. Using two different approaches, we derive upper…

Probability · Mathematics 2020-09-29 Masakiyo Miyazawa

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

We study Markov processes where the "time" parameter is replaced by paths in a directed graph from an initial vertex to a terminal one. Along each directed path the process is Markov and has the same distribution as the one along any other…

Probability · Mathematics 2012-11-16 Krzysztof Burdzy , Soumik Pal

In this paper, we consider a class of inhomogeneous semi-Markov processes directly based on intensity processes for marked point processes. We show that this class satisfies the semi-Markov properties defined elsewhere in the literature. We…

Probability · Mathematics 2015-04-14 Alexander Sokol

We discuss the concepts of quasi-renewal and quasi-regenerative processes. We also propose a method for obtaining the upper bounds for the convergence rate of the distribution of a regenerative and quasi-regenerative process to a stationary…

Probability · Mathematics 2023-05-24 Galina A. Zverkina

In this paper, we establish some functional central limit theorems for a large class of general supercritical superprocesses with spatially dependent branching mechanisms satisfying a second moment condition. In the particular case when the…

Probability · Mathematics 2014-10-08 Yan-Xia Ren , Renming Song , Rui Zhang

Using the age-structure formalism, we definitely establish connections between semi-Markov processes and the dynamics of open quantum systems that satisfy the Markov quantum master equations. A generalized Feynman-Kac formula of the…

Statistical Mechanics · Physics 2022-12-07 Fei Liu

We prove an invariance principle (functional central limit theorem) for a vector-valued additive functional of a Markov chain for almost every starting point with respect to an ergodic equilibrium distribution. The hypothesis is a moment…

Probability · Mathematics 2011-10-20 F. Rassoul-Agha , T. Seppalainen

Semi-Markov processes generalize Markov processes by adding temporal memory effects as expressed by a semi-Markov kernel. We recall the path weight for a semi-Markov trajectory and the fact that thermodynamic consistency in equilibrium…

Statistical Mechanics · Physics 2022-04-15 Benjamin Ertel , Jann van der Meer , Udo Seifert

In this paper we consider a control problem for a Partially Observable Piecewise Deterministic Markov Process of the following type: After the jump of the process the controller receives a noisy signal about the state and the aim is to…

Optimization and Control · Mathematics 2021-07-21 Nicole Bäuerle , Dirk Lange

The theory of ``Markov-up'' processes is being developed. This is a new class of stochastic processes with ``partial'' markovian features; it could also be called ``one-sided Markov''. Such a behavior may be found in the real world and in…

Probability · Mathematics 2024-07-01 D. O. Kalikaeva

This paper focuses on a class of continuous-time controlled Markov chains with time-inconsistent and distribution-dependent cost functional (in some appropriate sense). A new definition of time-inconsistent distribution-dependent…

Optimization and Control · Mathematics 2019-09-26 Hongwei Mei , George Yin

The topic of this manuscript is the stability analysis of continuous-time switched nonlinear systems with constraints on the admissible switching signals. Our particular focus lies in considering signals characterized by upper and lower…

Optimization and Control · Mathematics 2024-01-17 Matteo Della Rossa

In this paper, we derive a simple drift condition for the stability of a class of two-dimensional Markov processes, for which one of the coordinates (also referred to as the {\em phase} for convenience) has a well understood behaviour…

Probability · Mathematics 2020-10-01 Stella Kapodistria , Seva Shneer

Intermediately subcritical branching processes in random environment are at the borderline between two subcritical regimes and exhibit a particularly rich behavior. In this paper, we prove a functional limit theorem for these processes. It…

Probability · Mathematics 2012-09-07 Christian Böinghoff , Götz Kersting

We give a short overview of recent results on a specific class of Markov process: the Piecewise Deterministic Markov Processes (PDMPs). We first recall the definition of these processes and give some general results. On more specific cases…

Statistics Theory · Mathematics 2013-09-25 Romain Azaïs , Jean-Baptiste Bardet , Alexandre Genadot , Nathalie Krell , Pierre-André Zitt
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