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We provide a Poisson approximation result for dependent thinnings of Gibbs point processes as well as qualitative and quantitative central limit theorems for geometric functionals of Gibbs point processes in increasing observation windows.…

Probability · Mathematics 2026-01-27 Christian Hirsch , Moritz Otto , Anne Marie Svane

We prove a Poisson process approximation result for stabilizing functionals of a determinantal point process. Our results use concrete couplings of determinantal processes with different Palm measures and exploit their association…

Probability · Mathematics 2024-02-14 Moritz Otto

We generalise disagreement percolation to Gibbs point processes of balls with varying radii. This allows to establish the uniqueness of the Gibbs measure and exponential decay of pair correlations in the low activity regime by comparison…

Probability · Mathematics 2019-04-24 Christoph Hofer-Temmel , Pierre Houdebert

We establish inequalities for assessing the distance between the distribution of a (possibly multidimensional) functional of a Poisson random measure and that of a Gaussian element. Our bounds only involve add-one cost operators at the…

Probability · Mathematics 2020-10-27 Raphaël Lachièze-Rey , Giovanni Peccati , Xiaochuan Yang

We present new Poisson process approximation results for stabilizing functionals of Poisson and binomial point processes. These functionals are allowed to have an unbounded range of interaction and encompass many examples in stochastic…

Probability · Mathematics 2021-04-28 Omer Bobrowski , Matthias Schulte , D. Yogeshwaran

We study a stationary Gibbs particle process with deterministically bounded particles on Euclidean space defined in terms of an activity parameter and non-negative interaction potentials of finite range. Using disagreement percolation we…

Probability · Mathematics 2020-09-08 Viktor Beneš , Christoph Hofer-Temmel , Günter Last , Jakub Večeřa

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

Central limit theorems (CLTs) have a long history in probability and statistics. They play a fundamental role in constructing valid statistical inference procedures. Over the last century, various techniques have been developed in…

Statistics Theory · Mathematics 2023-06-27 Arisina Banerjee , Arun K Kuchibhotla

Statistical inference for non-stationary data is hindered by the failure of classical central limit theorems (CLTs), not least because there is no fixed Gaussian limit to converge to. To resolve this, we introduce relative weak convergence,…

Statistics Theory · Mathematics 2025-10-28 Nicolai Palm , Thomas Nagler

We present a new and simple approach to concentration inequalities for functions around their expectation with respect to non-product measures, i.e., for dependent random variables. Our method is based on coupling ideas and does not use…

Probability · Mathematics 2007-05-23 J. -R. Chazottes , P. Collet , C. Kuelske , F. Redig

The paper deals with a random connection model, a random graph whose vertices are given by a homogeneous Poisson point process on $\mathbb{R}^d$, and edges are independently drawn with probability depending on the locations of the two end…

Probability · Mathematics 2021-02-18 Van Hao Can , Khanh Duy Trinh

This paper is concerned with statistical inference for infinite range interaction Gibbs point processes and in particular for the large class of Ruelle superstable and lower regular pairwise interaction models. We extend classical…

Statistics Theory · Mathematics 2015-10-05 Jean-François Coeurjolly , Frédéric Lavancier

The purpose of the present paper is to establish explicit bounds on moderate deviation probabilities for a rather general class of geometric functionals enjoying the stabilization property, under Poisson input and the assumption of a…

Probability · Mathematics 2015-03-17 Peter Eichelsbacher , Martin Raic , Tomasz Schreiber

Disagreement percolation connects a Gibbs lattice gas and i.i.d. site percolation on the same lattice such that non-percolation implies uniqueness of the Gibbs measure. This work generalises disagreement percolation to the hard-sphere model…

Probability · Mathematics 2019-07-02 Christoph Hofer-Temmel

The purpose of this paper is to provide a first class of explicit sufficient conditions for the central limit theorem and related results in the setup of non-uniformly (partially) expanding non iid random transformations, considered as…

Dynamical Systems · Mathematics 2023-07-25 Yeor Hafouta

We discuss a thinning and an embedding procedure to construct finite Gibbs processes with a given Papangelou intensity. Extending the approach in Hofer-Temmel (2019) and Hofer-Temmel and Houdebert (2019) we will use this to couple two…

Probability · Mathematics 2023-01-24 Günter Last , Moritz Otto

The question of whether the central limit theorem (CLT) holds for the total number of edges in exponential random graph models (ERGMs) in the subcritical region of parameters has remained an open problem. In this paper, we establish the…

Probability · Mathematics 2025-04-09 Xiao Fang , Song-Hao Liu , Qi-Man Shao , Yi-Kun Zhao

Given a Gibbs point process $\P^{\Psi}$ on $\R^d$ having a weak enough potential $\Psi$, we consider the random measures $\mu_\la := \sum_{x \in \P^{\Psi} \cap Q_\la} \xi(x, \P^{\Psi} \cap Q_\la) \delta_{x/\la^{1/d}}$, where $Q_{\la} :=…

Probability · Mathematics 2008-02-06 T. Schreiber , J. E. Yukich

Drees and Rootz\'en [2010] have proven central limit theorems (CLT) for empirical processes of extreme values cluster functionals built from $\beta$-mixing processes. The problem with this family of $\beta$-mixing processes is that it is…

Probability · Mathematics 2015-11-24 José Gregorio Gómez

We establish new explicit bounds on the Gaussian approximation of Poisson functionals based on novel estimates of moments of Skorohod integrals. Combining these with the Malliavin-Stein method, we derive bounds in the Wasserstein and…

Probability · Mathematics 2022-12-08 Tara Trauthwein
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