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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 investigate the hyperuniformity of marked Gibbs point processes with weak dependencies among distant points whilst the interactions of close points are kept arbitrary. Some variants of stability and range assumptions are posed on the…

Probability · Mathematics 2024-01-17 David Dereudre , Daniela Flimmel

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

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

The intensity of a Gibbs point process is usually an intractable function of the model parameters. For repulsive pairwise interaction point processes, this intensity can be expressed as the Laplace transform of some particular function.…

Methodology · Statistics 2017-12-11 Jean-François Coeurjolly , Frédéric Lavancier

Deriving exact density functions for Gibbs point processes has been challenging due to their general intractability, stemming from the intractability of their normalising constants/partition functions. This paper offers a solution to this…

Probability · Mathematics 2024-06-12 Ottmar Cronie

In this paper, we want to clarify the Gibbs phenomenon when continuous and discontinuous finite elements are used to approximate discontinuous or nearly discontinuous PDE solutions from the approximation point of view. For a simple step…

Numerical Analysis · Mathematics 2022-08-03 Shun Zhang

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 study a local thinning $T_r$ that retains a point with probability $p(n_r)$, where $n_r$ counts neighbors within radius $r$. For Poisson input with spatially varying intensity, we obtain an exact intensity via a Poisson--mixture formula…

Probability · Mathematics 2025-11-14 Kateryna Hlyniana

A new type of dependent thinning for point processes in continuous space is proposed, which leverages the advantages of determinantal point processes defined on finite spaces and, as such, is particularly amenable to statistical, numerical,…

Machine Learning · Computer Science 2019-06-19 Bartłomiej Błaszczyszyn , Paul Keeler

We derive explicit lower and upper bounds for the probability generating functional of a stationary locally stable Gibbs point process, which can be applied to summary statistics like the F function. For pairwise interaction processes we…

Probability · Mathematics 2013-04-18 Kaspar Stucki , Dominic Schuhmacher

We consider the Gibbs measure of a general interacting particle system for a certain class of ``weakly interacting" kernels. In particular, we show that the local point process converges to a Poisson point process as long as the inverse…

Probability · Mathematics 2025-06-18 David Padilla-Garza , Luke Peilen , Eric Thoma

In this paper, we apply the Stein's method in the context of point processes, namely when the target measure is the distribution of a finite Poisson point process. We show that the so-called Kantorovich-Rubinstein distance between such a…

Probability · Mathematics 2018-07-09 Laurent Decreusefond , Aurélien Vasseur

A central task in many applications is reasoning about processes that change over continuous time. Continuous-Time Bayesian Networks is a general compact representation language for multi-component continuous-time processes. However, exact…

Artificial Intelligence · Computer Science 2012-06-18 Tal El-Hay , Nir Friedman , Raz Kupferman

We construct marked Gibbs point processes in $\mathbb{R}^d$ under quite general assumptions. Firstly, we allow for interaction functionals that may be unbounded and whose range is not assumed to be uniformly bounded. Indeed, our typical…

Probability · Mathematics 2022-07-15 Sylvie Roelly , Alexander Zass

In this paper we address the questions of perfectly sampling a Gibbs measure with infinite range interactions and of perfectly sampling the measure together with its finite range approximations. We solve these questions by introducing a…

Probability · Mathematics 2015-05-13 Antonio Galves , Eva Loecherbach , Enza Orlandi

Let Pi and Gamma be homogeneous Poisson point processes on a fixed set of finite volume. We prove a necessary and sufficient condition on the two intensities for the existence of a coupling of Pi and Gamma such that Gamma is a deterministic…

Probability · Mathematics 2009-12-02 Omer Angel , Alexander E. Holroyd , Terry Soo

It is well known that a binomial $(n,p)$ can be approximated by a Poisson distribution with parameter $np$. The typical approach in undergraduate probability texts is to show a convergence result for the distribution of the binomial as $n$…

Probability · Mathematics 2026-05-05 Rinaldo B. Schinazi

We explore two aspects of geometric approximation via a coupling approach to Stein's method. Firstly, we refine precision and increase scope for applications by convoluting the approximating geometric distribution with a simple translation…

Probability · Mathematics 2024-12-11 Fraser Daly , Claude Lefèvre

We establish Poisson and compound Poisson approximations for stabilizing statistics of $\beta$-mixing point processes and give explicit rates of convergence. Our findings are based on a general estimate of the total variation distance of a…

Probability · Mathematics 2023-10-24 Nicolas Chenavier , Moritz Otto
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