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In this article, we fill a gap in the literature regarding quantitative functional central limit theorems (qfCLT) for Hawkes processes by providing an upper bound for the convergence of a nearly unstable Hawkes process toward a…

Probability · Mathematics 2025-06-16 Laure Coutin , Benjamin Massat , Anthony Réveillac

Let $\xi$ be the stationary occupation field generated by a Poisson system of independent simple symmetric random walks on $\mathbb Z$ in space--time dimension $1+1$. For a finite set $A\subset\mathbb Z$, we consider the classical…

Probability · Mathematics 2026-03-17 Ao Huang , Guanglin Rang , Zhonggen Su

A class of improved estimators is proposed for N-point correlation functions of galaxy clustering, and for discrete spatial random processes in general. In the limit of weak clustering, the variance of the unbiased estimator converges to…

Astrophysics · Physics 2007-05-23 István Szapudi , Alexander S. Szalay

We study a general non-homogeneous Skellam-type process with jumps of arbitrary fixed size. We express this process in terms of a linear combination of Poisson processes and study several properties, including the summation of independent…

Probability · Mathematics 2025-04-11 Fabrizio Cinque , Enzo Orsingher

What constitutes jointly Poisson processes remains an unresolved issue. This report reviews the current state of the theory and indicates how the accepted but unproven model equals that resulting from the small time-interval limit of…

Data Analysis, Statistics and Probability · Physics 2009-11-16 D. H. Johnson , I. N. Goodman

For a determinantal point process $X$ with a kernel $K$ whose spectrum is strictly less than one, Andr{\'e} Goldman has established a coupling to its reduced Palm process $X^u$ at a point $u$ with $K(u,u)>0$ so that almost surely $X^u$ is…

Probability · Mathematics 2020-10-06 Jesper Møller , Eliza O'Reilly

The main purpose of this paper is to investigate the strong approximation of the $p$-fold integrated empirical process, $p$ being a fixed positive integer. More precisely, we obtain the exact rate of the approximations by a sequence of…

Statistics Theory · Mathematics 2019-03-15 Sergio Alvarez-Andrade , Salim Bouzebda , Aimé Lachal

We construct a family of processes, from a single Poisson process, that converges in law to a complex Brownian motion. Moreover, we find realizations of these processes that converge almost surely to the complex Brownian motion, uniformly…

Probability · Mathematics 2015-09-25 Xavier Bardina , Giulia Binotto , Carles Rovira

We prove limit theorems for functionals of a Poisson point process using the Malliavin calculus on the Poisson space. The target distribution is conditionally either a Gaussian vector or a Poisson random variable. The convergence is stable…

Probability · Mathematics 2024-06-21 Ronan Herry

This work investigates the properties of the proximity operator for quasar-convex functions and establishes the convergence of the proximal point algorithm to a global minimizer with a particular focus on its convergence rate. In…

Optimization and Control · Mathematics 2026-04-16 José de Brito , Felipe Lara , Di Liu

It is well known that one can map certain properties of random matrices, fermionic gases, and zeros of the Riemann zeta function to a unique point process on the real line. Here we analytically provide exact generalizations of such a point…

Statistical Mechanics · Physics 2009-11-13 Salvatore Torquato , A. Scardicchio , Chase E Zachary

Project a collection of points on the high-dimensional sphere onto a random direction. If most of the points are sufficiently far from one another in an appropriate sense, the projection is locally close in distribution to the Poisson point…

Probability · Mathematics 2011-06-27 Itai Benjamini , Oded Schramm , Sasha Sodin

We propose a method for solving constrained fixed point problems involving compositions of Lipschitz pseudo contractive and firmly nonexpansive operators in Hilbert spaces. Each iteration of the method uses separate evaluations of these…

Optimization and Control · Mathematics 2011-01-10 Luis M. Briceño-Arias

Piecewise deterministic Markov processes (PDMPs) are a class of stochastic processes with applications in several fields of applied mathematics spanning from mathematical modeling of physical phenomena to computational methods. A PDMP is…

Probability · Mathematics 2022-09-30 Andrea Bertazzi , Joris Bierkens , Paul Dobson

We characterize the statistics of nearest-neighbor and contact distance distributions for Thomas cluster process (TCP), which is a special case of Poisson cluster process. In particular, we derive the cumulative distribution function (CDF)…

Information Theory · Computer Science 2016-09-27 Mehrnaz Afshang , Chiranjib Saha , Harpreet S. Dhillon

We define a time dependent empirical process based on $n$ i.i.d.~fractional Brownian motions and establish Gaussian couplings and strong approximations to it by Gaussian processes. They lead to functional laws of the iterated logarithm for…

Probability · Mathematics 2016-06-21 Péter Kevei , David M. Mason

We generalize the Poisson limit theorem to binary functions of random objects whose law is invariant under the action of an amenable group. Examples include stationary random fields, exchangeable sequences, and exchangeable graphs. A…

Probability · Mathematics 2024-01-19 Haoyu Ye , Peter Orbanz , Morgane Austern

We develop a pseudo-metric analogue of bisimulation for generalized semi-Markov processes. The kernel of this pseudo-metric corresponds to bisimulation; thus we have extended bisimulation for continuous-time probabilistic processes to a…

Logic in Computer Science · Computer Science 2017-01-11 Vineet Gupta , Radha Jagadeesan , Prakash Panangaden

We investigate continuum percolation for Cox point processes, that is, Poisson point processes driven by random intensity measures. First, we derive sufficient conditions for the existence of non-trivial sub- and super-critical percolation…

Probability · Mathematics 2017-11-01 Christian Hirsch , Benedikt Jahnel , Elie Cali

We study the problem of non-parametric Bayesian estimation of the intensity function of a Poisson point process. The observations are $n$ independent realisations of a Poisson point process on the interval $[0,T]$. We propose two related…

Methodology · Statistics 2020-03-31 Shota Gugushvili , Frank van der Meulen , Moritz Schauer , Peter Spreij
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