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In this paper, we establish a version of the central limit theorem for Markov-Feller continuous time processes (with a Polish state space) that are exponentially ergodic in the bounded-Lipschitz distance and enjoy a continuous form of the…

Probability · Mathematics 2023-10-09 Dawid Czapla , Katarzyna Horbacz , Hanna Wojewódka-Ściążko

We consider zero-range processes in ${\mathbb{Z}}^d$ with site dependent jump rates. The rate for a particle jump from site $x$ to $y$ in ${\mathbb{Z}}^d$ is given by $\lambda_xg(k)p(y-x)$, where $p(\cdot)$ is a probability in…

Probability · Mathematics 2007-09-12 Pablo A. Ferrari , Valentin V. Sisko

The presence of temporal correlations in random movement trajectories is a widespread phenomenon across biological, chemical and physical systems. The ubiquity of persistent and anti-persistent motion in many natural and synthetic systems…

Statistical Mechanics · Physics 2024-07-03 Daniel Marris , Luca Giuggioli

A rescaled Markov chain converges uniformly in probability to the solution of an ordinary differential equation, under carefully specified assumptions. The presentation is much simpler than those in the outside literature. The result may be…

Probability · Mathematics 2007-05-23 R. W. R. Darling

We consider random walks on marked simple point processes with symmetric jump rates and unbounded jump range. We prove homogenization properties of the associated Markov generators. As an application, we derive the hydrodynamic limit of the…

Probability · Mathematics 2020-09-17 A. Faggionato

Continuous-time Mallows processes are processes of random permutations of the set $\{1, \ldots, n\}$ whose marginal at time $t$ is the Mallows distribution with parameter $t$. Recently Corsini showed that there exists a unique Markov…

Probability · Mathematics 2024-04-15 Radosław Adamczak , Michał Kotowski

Max-stable processes are widely used to model spatial extremes. These processes exhibit asymptotic dependence meaning that the large values of the process can occur simultaneously over space. Recently, inverted max-stable processes have…

Probability · Mathematics 2015-01-20 Ioannis Papastathopoulos , Jonathan A. Tawn

The molecular evolution in a gene regulatory network is classically modeled by Markov jump processes. However, the direct simulation of such models is extremely time consuming. Indeed, even the simplest Markovian model, such as the…

Probability · Mathematics 2012-11-30 Aurélie Muller-Gueudin

We propose a method for approximating solutions to optimization problems involving the global stability properties of parameter-dependent continuous-time autonomous dynamical systems. The method relies on an approximation of the…

Optimization and Control · Mathematics 2013-08-12 Péter Koltai , Alexander Volf

Markov jump processes (MJPs) are used to model a wide range of phenomena from disease progression to RNA path folding. However, maximum likelihood estimation of parametric models leads to degenerate trajectories and inferential performance…

Machine Learning · Statistics 2015-06-08 Jonathan H. Huggins , Karthik Narasimhan , Ardavan Saeedi , Vikash K. Mansinghka

Consider a sequence (Z_n,Z_n^M) of bivariate L\'evy processes, such that Z_n is a spectrally positive L\'evy process with finite variation, and Z_n^M is the counting process of marks in {0,1} carried by the jumps of Z_n. The study of these…

Probability · Mathematics 2014-03-11 Cécile Delaporte

We study the asymptotic behaviour of a version of the one-dimensional Mott random walk in a regime that exhibits severe blocking. We establish that, for any fixed time, the appropriately-rescaled Mott random walk is situated between two…

Probability · Mathematics 2024-04-19 David A. Croydon , Ryoki Fukushima , Stefan Junk

In this paper, we are interested in the exact simulation of a class of Piecewise Deterministic Markov Processes (PDMP). We show how to perform efficient thinning algorithms depending on the jump rate bound. For different types of jump rate…

Probability · Mathematics 2022-02-10 Vincent Lemaire , Michèle Thieullen , Nicolas Thomas

This paper presents a nonparametric method for estimating the conditional density associated to the jump rate of a piecewise-deterministic Markov process. In our framework, the estimation needs only one observation of the process within a…

Statistics Theory · Mathematics 2012-07-12 Romain Azaïs , François Dufour , Anne Gégout-Petit

With many Hamiltonians one can naturally associate a |Psi|^2-distributed Markov process. For nonrelativistic quantum mechanics, this process is in fact deterministic, and is known as Bohmian mechanics. For the Hamiltonian of a quantum field…

Quantum Physics · Physics 2007-05-23 Detlef Duerr , Sheldon Goldstein , Roderich Tumulka , Nino Zanghi

We prove the global asymptotic equivalence between the experiments generated by the discrete (high frequency) or continuous observation of a path of a time inhomogeneous jump-diffusion process and a Gaussian white noise experiment. Here,…

Probability · Mathematics 2015-03-24 Ester Mariucci

We consider a general d-dimensional Levy-type process with killing. Combining the classical Dyson series approach with a novel polynomial expansion of the generator A(t) of the Levy-type process, we derive a family of asymptotic…

Computational Finance · Quantitative Finance 2014-12-01 Matthew Lorig , Stefano Pagliarani , Andrea Pascucci

The purpose of this paper is to ensure the conditions of G\"artner-Ellis Theorem for evaluations of the empirical measure. We show that up-to-date conditions for ensuring the convergence to a quasi-stationary distribution can be applied…

Probability · Mathematics 2020-04-21 Aurélien Velleret

First-passage properties of continuous stochastic processes confined in a 1--dimensional interval are well described. However, for jump processes (discrete random walks), the characterization of the corresponding observables remains…

Statistical Mechanics · Physics 2023-05-17 Jérémie Klinger , Raphaël Voituriez , Olivier Bénichou

An autoregressive process with Markov regime is an autoregressive process for which the regression function at each time point is given by a nonobservable Markov chain. In this paper we consider the asymptotic properties of the maximum…

Statistics Theory · Mathematics 2007-06-13 Randal Douc , Eric Moulines , Tobias Ryden
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