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We study the stochastic diffusive limit of a kinetic radiative transfer equation, which is non-linear, involving a small parameter and perturbed by a smooth random term. Under an appropriate scaling for the small parameter, using a…

Analysis of PDEs · Mathematics 2014-05-13 Arnaud Debussche , Sylvain De Moor , Julien Vovelle

We consider a family of general branching processes with reproduction parameters depending on the age of the individual as well as the population age structure and a parameter $K$, which may represent the carrying capacity. These processes…

Probability · Mathematics 2019-02-06 Jie Yen Fan , Kais Hamza , Peter Jagers , Fima C. Klebaner

For a strictly stationary sequence of $\mathbb{R}_{+}^{d}$--valued random vectors we derive functional convergence of partial maxima stochastic processes under joint regular variation and weak dependence conditions. The limit process is an…

Probability · Mathematics 2016-07-14 Danijel Krizmanić

Fractional Poisson processes, a rapidly growing area of non-Markovian stochastic processes, are useful in statistics to describe data from counting processes when waiting times are not exponentially distributed. We show that the fractional…

Classical Analysis and ODEs · Mathematics 2013-10-14 Markus Kreer , Ayse Kizilersu , Anthony W. Thomas

Stochastic processes offer a flexible mathematical formalism to model and reason about systems. Most analysis tools, however, start from the premises that models are fully specified, so that any parameters controlling the system's dynamics…

Systems and Control · Computer Science 2017-01-11 Luca Bortolussi , Guido Sanguinetti

A multiplicative stochastic process with the lower bound lognormally distributed is investigated. For the process, the model is constructed, and its distribution function (involving four parameters) and the related statistical properties…

Data Analysis, Statistics and Probability · Physics 2024-01-19 Ken Yamamoto , Yoshihiro Yamazaki

In this paper we study an asymptotic expansion for the distribution of a random motion of a particle driven by a Markov process in diffusion approximation. We show that the singularly perturbed equation of a Markovian random motion can be…

Probability · Mathematics 2012-03-21 A. Pogorui

By using limit theorems of uniform mixing Markov processes and martingale difference sequences, the strong law of large numbers, central limit theorem, and the law of iterated logarithm are established for additive functionals of…

Probability · Mathematics 2019-04-08 Jianhai Bao , Feng-Yu Wang , Chenggui Yuan

We consider a certain sequence of random walks. The state space of the n-th random walk is the set of all strict partitions of n (that is, partitions without equal parts). We prove that, as n goes to infinity, these random walks converge to…

Probability · Mathematics 2010-11-16 Leonid Petrov

We prove the conjectured limiting normality for the number of crossings of a uniformly chosen set partition of [n] = {1,2,...,n}. The arguments use a novel stochastic representation and are also used to prove central limit theorems for the…

Combinatorics · Mathematics 2015-02-04 Bobbie Chern , Persi Diaconis , Daniel M. Kane , Robert C. Rhoades

This paper introduces several new classes of mathematical structures that have close connections with physics and with the theory of dynamical systems. The most general of these structures, called indivisible stochastic processes,…

Quantum Physics · Physics 2026-02-09 Jacob A. Barandes

The paper establishes a functional version of the Hoeffding combinatorial central limit theorem. First, a pre-limiting Gaussian process approximation is defined, and is shown to be at a distance of the order of the Lyapounov ratio from the…

Probability · Mathematics 2009-07-03 A. D. Barbour , Svante Janson

The methodology based on the random walk processes is adapted and applied to a comprehensive analysis of the statistical properties of the probability fluxes. To this aim we define a simple model of the Markovian stochastic dynamics on a…

Statistical Mechanics · Physics 2015-12-15 Przemyslaw Chelminiak , Michal Kurzynski

We consider a class of piecewise-deterministic Markov processes where the state evolves according to a linear dynamical system. This continuous time evolution is interspersed by discrete events that occur at random times and change (reset)…

Systems and Control · Computer Science 2017-11-15 Mohammad Soltani , Abhyudai Singh

We consider random permutations on $\Sn$ with logarithmic growing cycles weights and study asymptotic behavior as the length $n$ tends to infinity. We show that the cycle count process converges to a vector of independent Poisson variables…

Probability · Mathematics 2018-06-14 Nicolas Robles , Dirk Zeindler

Assume that a family of stochastic processes on some Polish space $E$ converges to a deterministic process; the convergence is in distribution (hence in probability) at every fixed point in time. This assumption holds for a large family of…

Dynamical Systems · Mathematics 2012-07-13 Michel Benaim , Jean-Yves Le Boudec

The main result of this paper is a functional limit theorem for the sine-process. In particular, we study the limit distribution, in the space of trajectories, for the number of particles in a growing interval. The sine-process has the…

Dynamical Systems · Mathematics 2018-01-12 Alexander I. Bufetov , Andrey V. Dymov

We prove distributional limit theorems and one-sided laws of the iterated logarithm for a class of positive, mixing, stationary, stochastic processes which contains those obtained from non-integrable observables over certain piecewise…

Dynamical Systems · Mathematics 2016-08-03 Jon. Aaronson , Roland Zweimüller

For a strictly stationary sequence of random variables we derive functional convergence of the joint partial sum and partial maxima process under joint regular variation with index $\alpha \in (0,2)$ and weak dependence conditions. The…

Probability · Mathematics 2019-10-08 Danijel Krizmanic

We combine the method of exchangeable pairs with Stein's method for functional approximation. As a result, we give a general linearity condition under which an abstract Gaussian approximation theorem for stochastic processes holds. We apply…

Probability · Mathematics 2020-10-22 Mikolaj J. Kasprzak
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