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We apply general moment identities for Poisson stochastic integrals with random integrands to the computation of the moments of Markovian growth-collapse processes. This extends existing formulas for mean and variance available in the…

Probability · Mathematics 2021-03-09 Nicolas Privault

We investigate the Poisson regression method for Markov and semi-Markov jump processes from a nonparametric angle, allowing the lengths of the time and duration intervals in the partition to vary with the number of observations. Imposing no…

Statistics Theory · Mathematics 2026-05-06 Martin Bladt , Rasmus Frigaard Lemvig

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

A simple model of the new notion of "Markov up" processes is proposed; its positive recurrence and ergodic properties are shown under the appropriate conditions.

Probability · Mathematics 2023-01-02 Alexander Veretennikov , Maria Veretennikova

We study K-processes, which are Markov processes in a denumerable state space, all of whose elements are stable, with the exception of a single state, starting from which the process enters finite sets of stable states with uniform…

Probability · Mathematics 2008-08-27 L. R. G. Fontes , P. Mathieu

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

Consider a Markov chain $\{X_n\}_{n\ge 0}$ with an ergodic probability measure $\pi$. Let $\Psi$ a function on the state space of the chain, with $\alpha$-tails with respect to $\pi$, $\alpha\in (0,2)$. We find sufficient conditions on the…

Probability · Mathematics 2009-12-15 Milton Jara , Tomasz Komorowski , Stefano Olla

We construct marked Gibbs point processes in $\mathbb{R}^d$ under quite general assumptions. Firstly, we allow for interaction functionals that may be unbounded and whose range is not assumed to be uniformly bounded. Indeed, our typical…

Probability · Mathematics 2022-07-15 Sylvie Roelly , Alexander Zass

We address a class of Markov jump linear systems that are characterized by the underlying Markov process being time-inhomogeneous with a priori unknown transition probabilities. Necessary and sufficient conditions for uniform stochastic…

Systems and Control · Computer Science 2014-11-24 Collin C. Lutz , Daniel J. Stilwell

The authors present a method of indicator random processes, applicable to constructing models of jump processes associated with diffusion process. Indicator random processes are processes that take only two values: 1 and 0, in accordance…

Dynamical Systems · Mathematics 2024-02-06 Valery Doobko , Elena Karachanskaya

We study time-changed Markov processes to speed up the convergence of Markov chain Monte Carlo (MCMC) algorithms. The time-changed process is defined by adjusting the speed of time of a base process via a user-chosen, state-dependent…

Computation · Statistics 2025-04-08 Andrea Bertazzi , Giorgos Vasdekis

We give a complete and unified description -- under some stability assumptions -- of the functional scaling limits associated with some persistent random walks for which the recurrent or transient type is studied in [1]. As a result, we…

Probability · Mathematics 2016-12-02 Peggy Cénac , Arnaud Le Ny , Basile De Loynes , Yoann Offret

We study scaling limits of non-increasing Markov chains with values in the set of non-negative integers, under the assumption that the large jump events are rare and happen at rates that behave like a negative power of the current state. We…

Probability · Mathematics 2012-01-06 Bénédicte Haas , Grégory Miermont

We prove a central limit type theorem for critical marked Hawkes processes. We study the case where the marks are i.i.d. with nonnegative values and their common distribution is either heavy tailed or has finite variance. The kernel…

Probability · Mathematics 2026-05-05 Anna Talarczyk

A family of continuous-state branching processes with immigration are constructed as the solution flow of a stochastic equation system driven by time-space noises. The family can be regarded as an inhomogeneous increasing path-valued…

Probability · Mathematics 2014-01-14 Zenghu Li

We consider sequences $(X_t^N)_{t\geq0}$ of Markov processes in two dimensions whose fluid limit is a stable solution of an ordinary differential equation of the form $\dot{x}_t=b(x_t)$, where $b(x)={\pmatrix{-\mu 0 0 \lambda}}x+\tau(x)$…

Probability · Mathematics 2011-11-10 Amanda G. Turner

In this paper, we explore the connection between convergence in distribution and Mallows distance in the context of positively associated random variables. Our results extend some known invariance principles for sequences with FKG property.…

Probability · Mathematics 2017-10-11 L. Cioletti , C. C. Y. Dorea , R. Vila

We introduce and study a family of Markov processes on partitions. The processes preserve the so-called z-measures on partitions previously studied in connection with harmonic analysis on the infinite symmetric group. We show that the…

Mathematical Physics · Physics 2007-05-23 Alexei Borodin , Grigori Olshanski

Using two simple examples, the continuous-time random walk as well as a two state Markov chain, the relation between generalized anomalous relaxation equations and semi-Markov processes is illustrated. This relation is then used to discuss…

Probability · Mathematics 2017-11-22 Enrico Scalas

We consider a Markovian evolution on point processes, the $\Psi$--process, on the unit interval in which points are added according to a rule that depends only on the spacings of the existing point configuration. Having chosen a spacing, a…

Probability · Mathematics 2020-07-01 Pascal Maillard , Elliot Paquette