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We construct a general stochastic process and prove weak convergence results. It is scaled in space and through the parameters of its distribution. We show that our simplified scaling is equivalent to time scaling used frequently. The…

Probability · Mathematics 2011-07-01 Mine Caglar

We consider the fully-coupled McKean-Vlasov equation with multi-time-scale potentials, and all the coefficients depend on the distributions of both the slow component and the fast motion. By studying the smoothness of the solution of the…

Probability · Mathematics 2022-04-28 Yun Li , Fuke Wu , Longjie Xie

We construct a compound Poisson process conditioned on its random summation that represents the sizes of the connected components in the sparse Erd\H{o}s-R\'enyi random graph $G(n,c/n)$. This new representation depicts a connection between…

Probability · Mathematics 2023-10-23 Wen Sun

Various phenomenological models of particle multiplicity distributions are discussed using a general form of the grand canonical partition function. These phenomenological models include a wide range of varied processes such as coherent…

Nuclear Theory · Physics 2007-05-23 S. J. Lee , A. Z. Mekjian

We consider the fragmentation process with mass loss and discuss self-similar properties of the arising structure both in time and space, focusing on dimensional analysis. This exhibits a spectrum of mass exponents $\theta$, whose exact…

Statistical Mechanics · Physics 2009-11-07 M. K. Hassan , J. Kurths

Homogeneous fragmentations describe the evolution of a unit mass that breaks down randomly into pieces as time passes. They can be thought of as continuous time analogs of a certain type of branching random walks, which suggests the use of…

Probability · Mathematics 2007-05-23 Jean Bertoin , Alain Rouault

This paper proposes a new methodology to perform Bayesian inference for a class of multidimensional Cox processes in which the intensity function is piecewise constant. Poisson processes with piecewise constant intensity functions are…

Methodology · Statistics 2022-11-16 Flavio B. Gonçalves , Barbara C. C. Dias

Motivated by Alain-Sol Sznitman's interlacement process, we consider the set of $\{0,1\}$-valued processes which can be constructed in an analogous way, namely as a union of sets coming from a Poisson process on a collection of sets. Our…

Probability · Mathematics 2025-06-03 Malin P. Forsström , Nina Gantert , Jeffrey E. Steif

Poisson processes and one-dimensional Poisson point processes satisfy three main properties: superposition, thinning, and conditioning. The proof of the first two relies on basic estimates involving the Poisson distribution that are also…

Probability · Mathematics 2025-09-01 Nicolas Lanchier

The Ewens-Pitman model is a probability distribution for random partitions of the set $[n]=\{1,\ldots,n\}$, parameterized by $\alpha\in[0,1)$ and $\theta>-\alpha$, with $\alpha=0$ corresponding to the Ewens model in population genetics. The…

Probability · Mathematics 2025-03-11 Bernard Bercu , Stefano Favaro

The binomial, the negative binomial, the Poisson, the compound Poisson and the Erlang distribution do all admit integral representations with respect to its (continuous) parameter. We use the Margulis-Russo type formulas for Bernoulli and…

Probability · Mathematics 2026-02-05 Guenter Last , Sergei Zuyev

The paper is concerned with the equilibrium distributions of continuous-time density dependent Markov processes on the integers. These distributions are known typically to be approximately normal, and the approximation error, as measured in…

Probability · Mathematics 2009-02-06 Sanda N. Socoll , A. D. Barbour

We define a Markov process on the partitions of $[n]=\{1,\ldots,n\}$ by drawing a sample in $[n]$ at each time of a Poisson process, by merging blocks that contain one of these points and by leaving all other blocks unchanged. This…

Probability · Mathematics 2018-09-03 Sophie Lemaire

Fragmentation processes are part of a broad class of models describing the evolution of a system of particles which split apart at random. These models are widely used in biology, materials science and nuclear physics, and their asymptotic…

Probability · Mathematics 2020-07-23 Quan Shi , Alexander R. Watson

In this paper we consider the relation between random sums and compositions of different processes. In particular, for independent Poisson processes $N_\alpha(t)$, $N_\beta(t)$, $t>0$, we show that $N_\alpha(N_\beta(t))…

Probability · Mathematics 2013-03-28 Enzo Orsingher , Federico Polito

Fractional generalizations of the Poisson process and branching Furry process are considered. The link between characteristics of the processes, fractional differential equations and Levy stable densities are discussed and used for…

Statistical Mechanics · Physics 2010-02-15 Vladimir V. Uchaikin , Dexter O. Cahoy , Renat T. Sibatov

The space-fractional and the time-fractional Poisson processes are two well-known models of fractional evolution. They can be constructed as standard Poisson processes with the time variable replaced by a stable subordinator and its…

Probability · Mathematics 2016-08-09 Luisa Beghin , Costantino Ricciuti

Fix a subset $S \subset \mathbb{R}^n$ of volume at most $c n$ that satisfies $S \cap (-S) = \emptyset$. We consider two point processes in $S$: the first is the Poisson point process of intensity one, and the second is the restriction of a…

Probability · Mathematics 2026-05-12 Boaz Klartag

This paper gives an elementary proof for the following theorem: a renewal process can be represented by a doubly-stochastic Poisson process (DSPP) if and only if the Laplace-Stieltjes transform of the inter-arrival times is of the following…

Probability · Mathematics 2024-09-30 Xinlong Du , Harsha Honnappa

Point processes are an essential tool when we are interested in where in time or space events occur. The basic starting point for point processes is usually the Poisson process. Over the years, Stein's method has been developed with a great…

Probability · Mathematics 2015-11-11 H. L. Gan