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Related papers: Some Compound Fractional Poisson Processes

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Fractional equations have become the model of choice in several applications where heterogeneities at the microstructure result in anomalous diffusive behavior at the macroscale. In this work we introduce a new fractional operator…

Numerical Analysis · Mathematics 2021-01-29 Marta D'Elia , Christian Glusa

In this paper we give a historical account of the development of Poisson approximation using Stein's method and present some of the main results. We give two recent applications, one on maximal arithmetic progressions and the other on…

Probability · Mathematics 2013-10-09 Louis H. Y. Chen , Adrian Röllin

In this paper we consider the Riemann--Liouville fractional integral $\mathcal{N}^{\alpha,\nu}(t)= \frac{1}{\Gamma(\alpha)} \int_0^t (t-s)^{\alpha-1}N^\nu(s) \, \mathrm ds $, where $N^\nu(t)$, $t \ge 0$, is a fractional Poisson process of…

Probability · Mathematics 2014-03-06 Enzo Orsingher , Federico Polito

The purpose of this work is to describe a unified, and indeed simple, mechanism for non-parametric Bayesian analysis, construction and generative sampling of a large class of latent feature models which one can describe as generalized…

Statistics Theory · Mathematics 2014-12-23 Lancelot F. James

The two parameter Poisson-Dirichlet Process (PDP), a generalisation of the Dirichlet Process, is increasingly being used for probabilistic modelling in discrete areas such as language technology, bioinformatics, and image analysis. There is…

Statistics Theory · Mathematics 2012-02-17 Wray Buntine , Marcus Hutter

We present the first fully variational Bayesian inference scheme for continuous Gaussian-process-modulated Poisson processes. Such point processes are used in a variety of domains, including neuroscience, geo-statistics and astronomy, but…

Machine Learning · Statistics 2015-07-29 Chris Lloyd , Tom Gunter , Michael A. Osborne , Stephen J. Roberts

Stationary stochastic processes with independent increments, of which the Poisson process is a prominent example, are widely used to describe real world events. With the basic assumption that a counting process is stationary and has…

Probability · Mathematics 2018-11-20 Enzhi Li

In the first part of this paper, we express the generalized Bessel function associated with dihedral systems and a constant multiplicity function as a infinite series of confluent Horn functions. The key ingredient leading to this…

Classical Analysis and ODEs · Mathematics 2020-09-02 Luc Deleaval , Nizar Demni

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

Fractional calculus has been used to describe physical systems with complexity. Here, we show that a fractional calculus approach can restore or include complexity in any physical systems that can be described by partial differential…

Mesoscale and Nanoscale Physics · Physics 2024-08-06 Kyle Rockwell , Ezio Iacocca

In this paper, we study the merging and splitting of generalized counting processes (GCPs). First, we study the merging of a finite number of independent GCPs and then extend it to the case of countably infinite. The merged process is…

Probability · Mathematics 2025-01-16 M. Dhillon , K. K. Kataria

We develop walk-on-sphere for fractional Poisson equations with Dirichilet boundary conditions in high dimensions. The walk-on-sphere method is based on probabilistic represen tation of the fractional Poisson equation. We propose effcient…

Numerical Analysis · Mathematics 2022-08-16 Caiyu Jiao , Changpin Li , Hexiang Wang , Zhongqiang Zhang

In [Schuhmacher, Electron. J. Probab. 10 (2005), 165--201] estimates of the Barbour-Brown distance d_2 between the distribution of a thinned point process and the distribution of a Poisson process were derived by combining discretization…

Probability · Mathematics 2007-05-23 Dominic Schuhmacher

We derive a moment formula for generalized fractional polynomial processes, i.e., for polynomial-preserving Markov processes time-changed by an inverse L\'evy-subordinator. If the time change is inverse $\alpha$-stable, the time-derivative…

Probability · Mathematics 2026-02-27 Johannes Assefa , Martin Keller-Ressel

Poisson's equation is fundamental to the study of Markov chains, and arises in connection with martingale representations and central limit theorems for additive functionals, perturbation theory for stationary distributions, and average…

Probability · Mathematics 2025-04-03 Peter W. Glynn , Na Lin , Yuanyuan Liu

Although the study of weak convergence of superpositions of point processes to the Poisson process dates back to the work of Grigelionis in 1963, it was only recently that Schuhmacher [Stochastic Process. Appl. 115 (2005) 1819--1837]…

Probability · Mathematics 2011-05-10 Louis H. Y. Chen , Aihua Xia

An information-theoretic development is given for the problem of compound Poisson approximation, which parallels earlier treatments for Gaussian and Poisson approximation. Let $P_{S_n}$ be the distribution of a sum $S_n=\Sumn Y_i$ of…

Probability · Mathematics 2019-06-05 A. D. Barbour , Oliver Johnson , Ioannis Kontoyiannis , Mokshay Madiman

In the paper we study the models of time-changed Poisson and Skellam-type processes, where the role of time is played by compound Poisson-Gamma subordinators and their inverse (or first passage time) processes. We obtain explicitly the…

Probability · Mathematics 2017-07-04 Khrystyna Buchak , Lyudmyla Sakhno

We discuss interplays between log-concave functions and log-concave sequences. We prove a Bernstein-type theorem, which characterizes the Laplace transform of log-concave measures on the half-line in terms of log-concavity of the…

Probability · Mathematics 2018-07-10 Bo'az Klartag , Joseph Lehec

The diffraction of various random subsets of the integer lattice $\mathbb{Z}^{d}$, such as the coin tossing and related systems, are well understood. Here, we go one important step beyond and consider random point sets in $\mathbb{R}^{d}$.…

Mathematical Physics · Physics 2011-05-18 Michael Baake , Holger Koesters