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We derive explicit formulas for probabilities of Brownian motion with jumps crossing linear or piecewise linear boundaries in any finite interval. We then use these formulas to approximate the boundary crossing probabilities for general…

Probability · Mathematics 2012-05-16 Jinghai Shao , Liqun Wang

We construct optimal Markov couplings of L\'{e}vy processes, whose L\'evy (jump) measure has an absolutely continuous component. The construction is based on properties of subordinate Brownian motions and the coupling of Brownian motions by…

Probability · Mathematics 2011-05-17 Björn Böttcher , René L. Schilling , Jian Wang

We derive a universal, exact asymptotic form of the splitting probability for symmetric continuous jump processes, which quantifies the probability $ \pi_{0,\underline{x}}(x_0)$ that the process crosses $x$ before 0 starting from a given…

Statistical Mechanics · Physics 2022-10-12 Jérémie Klinger , Raphaël Voituriez , Olivier Bénichou

We present an explicit construction of a Markovian random growth process on integer partitions such that given it visits some level $n$, it passes through any partition $\lambda$ of $n$ with equal probabilities. The construction has…

Probability · Mathematics 2024-10-01 Yuri Yakubovich

This paper is a variation on the uniform spanning tree theme. We use random spanning forests to solve the following problem: for a Markov process on a finite set of size $n$, find a probability law on the subsets of any given size $m \leq…

Probability · Mathematics 2016-02-01 Luca Avena , Alexandre Gaudillière

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

This paper presents a numerical method to calculate the value function for a general discounted impulse control problem for piecewise deterministic Markov processes. Our approach is based on a quantization technique for the underlying…

Probability · Mathematics 2011-08-31 Benoîte de Saporta , François Dufour

We give a bare-hands approach to the martingale representation theorem for integer valued random measures, which allows for a wide class of infinite activity jump processes, as well as all processes with well-ordered jumps.

Probability · Mathematics 2013-10-24 Samuel N. Cohen

We give general sufficient conditions to prove the convergence of marked point processes that keep record of the occurrence of rare events and of their impact for non-autonomous dynamical systems. We apply the results to sequential…

Dynamical Systems · Mathematics 2019-04-12 Ana Cristina Moreira Freitas , Jorge Milhazes Freitas , Mário Magalhães , Sandro Vaienti

We characterize the spectrum of the transition matrix for simple random walk on graphs consisting of a finite graph with a finite number of infinite Cayley trees attached. We show that there is a continuous spectrum identical to that for a…

Quantum Physics · Physics 2024-04-16 Bergfinnur Durhuus , Thordur Jonsson , John Wheater

This paper presents some general formulas for random partitions of a finite set derived by Kingman's model of random sampling from an interval partition generated by subintervals whose lengths are the points of a Poisson point process.…

Probability · Mathematics 2007-05-23 Jim Pitman

The aim of the present work is to show that the results obtained earlier on the approximation of distributions of sums of independent terms by the accompanying compound Poisson laws may be interpreted as rather sharp quantitative estimates…

Probability · Mathematics 2022-08-04 Friedrich Götze , Andrei Yu. Zaitsev

Existing results for the estimation of the L\'evy measure are mostly limited to the onedimensional setting. We apply the spectral method to multidimensional L\'evy processes in order to construct a nonparametric estimator for the…

Statistics Theory · Mathematics 2023-05-24 Maximilian F. Steffen

We consider a class of stochastic dynamical systems, called piecewise deterministic Markov processes, with states $(x, \s)\in \O\times \G$, $\O$ being a region in $\bbR^d$ or the $d$--dimensional torus, $\G$ being a finite set. The…

Statistical Mechanics · Physics 2009-02-25 Alessandra Faggionato , Davide Gabrielli , Marco Ribezzi Crivellari

In this paper we study coupled fully non-local equations, where a linear non-local operator jointly acts on the time and space variables. We establish existence and uniqueness of the solution. A maximum principle is proved and used to…

Probability · Mathematics 2025-01-24 Giacomo Ascione , Enrico Scalas , Bruno Toaldo , Lorenzo Torricelli

Most Markov chain Monte Carlo methods operate in discrete time and are reversible with respect to the target probability. Nevertheless, it is now understood that the use of non-reversible Markov chains can be beneficial in many contexts. In…

Methodology · Statistics 2021-02-23 Chris Sherlock , Alexandre H. Thiery

We study the solution $V$ of the Poisson equation $LV + f=0$ where $L$ is the backward generator of an irreducible (finite) Markov jump process and $f$ is a given centered state function. Bounds on $V$ are obtained using a graphical…

Probability · Mathematics 2024-04-04 Faezeh Khodabandehlou , Christian Maes , Karel Netočný

For Markov processes with absorption, we provide general criteria ensuring the existence and the exponential non-uniform convergence in total variation norm to a quasi-stationary distribution. We also characterize a subset of its domain of…

Probability · Mathematics 2022-10-24 Nicolas Champagnat , Denis Villemonais

This paper deals with the long run average continuous control problem of piecewise deterministic Markov processes (PDMP's) taking values in a general Borel space and with compact action space depending on the state variable. The control…

Probability · Mathematics 2008-09-03 O. L. V. Costa , F. Dufour

We consider random processes that are history-dependent, in the sense that the distribution of the next step of the process at any time depends upon the entire past history of the process. In general, therefore, the Markov property cannot…

Probability · Mathematics 2019-11-19 Peter Clifford , David Stirzaker