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We introduce a dynamic random hypergraph model constructed from a bipartite graph. In this model, both vertex sets of the bipartite graph are generated by marked Poisson point processes. Vertices of both vertex sets are equipped with marks…

Probability · Mathematics 2025-07-23 Christian Hirsch , Benedikt Jahnel , Péter Juhász

The convergence of a sequence of point processes with dependent points, defined by a symmetric function of iid high-dimensional random vectors, to a Poisson random measure is proved. This also implies the convergence of the joint…

Probability · Mathematics 2024-02-14 Johannes Heiny , Carolin Kleemann

In this paper we prove the Poisson Hypothesis for the limiting behavior of the large queueing systems in some simple ("mean-field") cases. We show in particular that the corresponding dynamical systems, defined by the non-linear Markov…

Mathematical Physics · Physics 2007-05-23 Alexander Rybko , Senya Shlosman

Let T be the homogeneous tree with degree and G a finitely generated group whose Cayley graph is T. The associated lamplighter group is the wreath product of the cyclic group of order r with G. For a large class of random walks on this…

Probability · Mathematics 2012-12-05 Anders Karlsson , Wolfgang Woess

This paper establishes expectation and variance asymptotics for statistics of the Poisson--Voronoi approximation of general sets, as the underlying intensity of the Poisson point process tends to infinity. Statistics of interest include…

Probability · Mathematics 2016-06-24 Christoph Thäle , J. E. Yukich

Limit theorems are presented for the rescaled occupation time fluctuation process of a critical finite variance branching particle system in $\mathbb{R}^{d}$ with symmetric $\alpha$-stable motion starting off from either a standard Poisson…

Probability · Mathematics 2009-11-04 Piotr Milos

Concentration inequalities for subgraph counts in random geometric graphs built over Poisson point processes are proved. The estimates give upper bounds for the probabilities $\mathbb{P}(N\geq M +r)$ and $\mathbb{P}(N\leq M - r)$ where $M$…

Probability · Mathematics 2015-04-29 Sascha Bachmann , Matthias Reitzner

The point process of vertices of an iteration infinitely divisible or more specifically of an iteration stable random tessellation in the Euclidean plane is considered. We explicitly determine its covariance measure and its pair-correlation…

Probability · Mathematics 2011-04-05 Tomasz Schreiber , Christoph Thaele

This paper deals with the quantitative normal approximation of non-linear functionals of Poisson random measures, where the quality is measured by the Kolmogorov distance. Combining Stein's method with the Malliavin calculus of variations…

Probability · Mathematics 2014-10-30 Peter Eichelsbacher , Christoph Thaele

A growing random graph is constructed by successively sampling without replacement an element from the pool of virtual vertices and edges. At start of the process the pool contains $N$ virtual vertices and no edges. Each time a vertex is…

Probability · Mathematics 2024-02-29 Michael Farber , Alexander Gnedin , Wajid Mannan

We consider a random geometric graph $G(\chi_n, r_n)$, given by connecting two vertices of a Poisson point process $\chi_n$ of intensity $n$ on the unit torus whenever their distance is smaller than the parameter $r_n$. The model is…

Probability · Mathematics 2019-07-04 Sourav Chatterjee , Matan Harel

We derive a central limit theorem for the number of vertices of convex polytopes induced by stationary Poisson hyperplane processes in $\mathbb{R}^d$. This result generalizes an earlier one proved by Paroux [Adv. in Appl. Probab. 30 (1998)…

Probability · Mathematics 2007-05-23 Lothar Heinrich , Hendrik Schmidt , Volker Schmidt

We prove a new class of inequalities, yielding bounds for the normal approximation in the Wasserstein and the Kolmogorov distance of functionals of a general Poisson process (Poisson random measure). Our approach is based on an iteration of…

Probability · Mathematics 2014-01-30 Günter Last , Giovanni Peccati , Matthias Schulte

This paper concerns the asymptotic behavior of a random variable $W_\lambda$ resulting from the summation of the functionals of a Gibbsian spatial point process over windows $Q_\lambda \uparrow R^d$. We establish conditions ensuring that…

Probability · Mathematics 2014-09-24 Aihua Xia , J. E. Yukich

We prove a general normal approximation theorem for local graph statistics in the configuration model, together with an explicit bound on the error in the approximation with respect to the Wasserstein metric. Such statistics take the form…

Probability · Mathematics 2019-03-19 A. D. Barbour , Adrian Röllin

We establish new lower bounds for the normal approximation in the Wasserstein distance of random variables that are functionals of a Poisson measure. Our results generalize previous findings by Nourdin and Peccati (2012, 2015) and Bierm\'e,…

Probability · Mathematics 2015-05-13 Ehsan Azmoodeh , Giovanni Peccati

In this article, we consider Poisson and Poisson convoluted geometric approximation to the sums of $n$ independent random variables under moment conditions. We use Stein's method to derive the approximation results in total variation…

Probability · Mathematics 2020-07-07 Pratima Eknath Kadu

We study the behavior of the random walk in a continuum independent long-range percolation model, in which two given vertices $x$ and $y$ are connected with probability that asymptotically behaves like $|x-y|^{-\alpha}$ with $\alpha>d$,…

Probability · Mathematics 2022-09-30 Ercan Sönmez , Arnaud Rousselle

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

[B{\l}aszczyszyn, Yogeshwaran and Yukich (2019)] established central limit theorems for geometric statistics of point processes having fast decay dependence. As limit theorems are of limited use unless we understand their errors involved in…

Probability · Mathematics 2022-05-27 Tianshu Cong , Aihua Xia
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