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We introduce a new framework that yields spectral bounds on norms of functions of transition maps for finite, homogeneous Markov chains. The techniques employed work for bounded semigroups, in particular for classical as well as for quantum…

Mathematical Physics · Physics 2015-03-16 Oleg Szehr , David Reeb , Michael M. Wolf

The embedding problem of Markov transition matrices into continuous-time Markov semigroups is a classic problem that regained a lot of impetus and activities in recent years. We consider it here for the following generalisation of the…

Probability · Mathematics 2026-01-27 Ellen Baake , Michael Baake

We consider Piecewise Deterministic Markov Processes (PDMPs) with a finite set of discrete states. In the regime of fast jumps between discrete states, we prove a law of large number and a large deviation principle. In the regime of fast…

Probability · Mathematics 2008-09-16 A. Faggionato , D. Gabrielli , M. Ribezzi Crivellari

In this paper we study the asymptotic behavior of linear processes having as innovations mean zero, square integrable functions of stationary reversible Markov chains. In doing so we shall preserve the generality of coefficients assuming…

Probability · Mathematics 2012-06-05 Magda Peligrad

We consider a finite or countable collection of one-dimensional Brownian particles whose dynamics at any point in time is determined by their rank in the entire particle system. Using Transportation Cost Inequalities for stochastic…

Probability · Mathematics 2010-11-11 Soumik Pal , Mykhaylo Shkolnikov

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

An explicit sufficient condition on the hypercontractivity is derived for the Markov semigroup associated to a class of functional stochastic differential equations. Consequently, the semigroup $P_t$ converges exponentially to its unique…

Probability · Mathematics 2014-09-19 Jianhai Bao , Feng-Yu Wang , Chenggui Yuan

In this paper we propose a new method for approximating the nonstationary moment dynamics of one dimensional Markovian birth-death processes. By expanding the transition probabilities of the Markov process in terms of Poisson-Charlier…

Numerical Analysis · Mathematics 2014-09-23 Stefan Engblom , Jamol Pender

Poissonian ensembles of Markov loops on a finite graph define a random graph process in which the addition of a loop can merge more than two connected components. We study Markov loops on the complete graph derived from a simple random walk…

Probability · Mathematics 2014-06-18 Sophie Lemaire

The article is devoted to the estimation of the rate of convergence of integral functionals of a Markov process. Under the assumption that the given Markov process admits a transition probability density which is differentiable in $t$ and…

Probability · Mathematics 2015-08-03 I. Ganychenko , V. Knopova , A. Kulik

For real-valued additive process $(X\_t)\_{t\geq 0}$ a recursive equation is derived for the entire positive moments of functionals $$I\_{s,t}= \int \_s^t\exp(-X\_u)du, \quad 0\leq s<t\leq\infty, $$ in case the Laplace exponent of $X\_t$…

Probability · Mathematics 2018-10-17 Paavo Salminen , Lioudmila Vostrikova

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

These lecture notes present some new concentration inequalities for Feynman-Kac particle processes. We analyze different types of stochastic particle models, including particle profile occupation measures, genealogical tree based evolution…

Numerical Analysis · Mathematics 2011-07-13 Pierre Del Moral , Peng Hu , Liming Wu

We study the Markov chain on $\mathbf{F}_p$ obtained by applying a function $f$ and adding $\pm\gamma$ with equal probability. When $f$ is a linear function, this is the well-studied Chung--Diaconis--Graham process. We consider two cases:…

Probability · Mathematics 2022-03-08 Jimmy He

Model reduction of Markov processes is a basic problem in modeling state-transition systems. Motivated by the state aggregation approach rooted in control theory, we study the statistical state compression of a discrete-state Markov chain…

Machine Learning · Statistics 2019-11-26 Anru Zhang , Mengdi Wang

This paper deals with ergodic theorems for particular time-inhomogeneous Markov processes, whose the time-inhomogeneity is asymptotically periodic. Under a Lyapunov/minorization condition, it is shown that, for any measurable bounded…

Probability · Mathematics 2022-04-06 William Oçafrain

In this paper, a class of piecewise deterministic Markov processes with underlying fast dynamic is studied. Using a "penalty method" , an averaging result is obtained when the underlying dynamic is infinitely accelerated. The features of…

Probability · Mathematics 2016-08-31 Alexandre Genadot

This paper presents new results on the Edgeworth expansion for high frequency functionals of continuous diffusion processes. We derive asymptotic expansions for weighted functionals of the Brownian motion and apply them to provide the…

Probability · Mathematics 2013-09-10 Mark Podolskij , Nakahiro Yoshida

This text is written based on the author's publications during the period from 1991 to 2001. The work is devoted to the theory of Markov intertwining operators and joinings of measure-preserving group actions, as well as to their…

Dynamical Systems · Mathematics 2021-03-15 Valery V. Ryzhikov

In order to give quantitative estimates for approximating the ergodic limit, we investigate probabilistic limit behaviors of time-averaging estimators of numerical discretizations for a class of time-homogeneous Markov processes, by…

Probability · Mathematics 2023-10-13 Chuchu Chen , Tonghe Dang , Jialin Hong , Guoting Song
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