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A workload model using the infinite source Poisson model for bursts is combined with the on--off model for within burst activity. Burst durations and on--off durations are assumed to have heavy-tailed distributions with infinite variance…

Statistics Theory · Mathematics 2011-06-06 David A. Rolls

In many contexts such as queuing theory, spatial statistics, geostatistics and meteorology, data are observed at irregular spatial positions. One model of this situation involves considering the observation points as generated by a Poisson…

Statistics Theory · Mathematics 2007-08-07 Tucker McElroy , Dimitris N. Politis

Random fields are useful mathematical tools for representing natural phenomena with complex dependence structures in space and/or time. In particular, the Gaussian random field is commonly used due to its attractive properties and…

The high-pressure compaction of three dimensional granular packings is simulated using a bonded particle model (BPM) to capture linear elastic deformation. In the model, grains are represented by a collection of point particles connected by…

Soft Condensed Matter · Physics 2023-10-19 Joel T. Clemmer , Joseph M. Monti , Jeremy B. Lechman

The paper considers the stationary Poisson Boolean model with spherical grains and proposes a family of nonparametric estimators for the radius distribution. These estimators are based on observed distances and radii, weighted in an…

Probability · Mathematics 2013-01-09 Daniel Hug , Günter Last , Zbyněk Pawlas , Wolfgang Weil

Let $k,d $ be positive integers. We determine a sequence of constants that are asymptotic to the probability that the cluster at the origin in a $d$-dimensional Poisson Boolean model with balls of fixed radius is of order $k$, as the…

Probability · Mathematics 2025-04-10 Mathew D. Penrose , Xiaochuan Yang

In this paper, we present a nonparametric method to estimate the heterogeneity of a random medium from the angular distribution of intensity transmitted through a slab of random material. Our approach is based on the modeling of forward…

Data Analysis, Statistics and Probability · Physics 2012-02-06 Nicolas Le Bihan , Ludovic Margerin

Random tessellations of the space represent a class of prototype models of heterogeneous media, which are central in several applications in physics, engineering and life sciences. In this work, we investigate the statistical properties of…

Statistical Mechanics · Physics 2016-07-25 Coline Larmier , Eric Dumonteil , Fausto Malvagi , Alain Mazzolo , Andrea Zoia

We present a general construction for dependent random measures based on thinning Poisson processes on an augmented space. The framework is not restricted to dependent versions of a specific nonparametric model, but can be applied to all…

Machine Learning · Statistics 2012-11-21 Nicholas J. Foti , Joseph D. Futoma , Daniel N. Rockmore , Sinead Williamson

Suppose that there are n bins, and balls arrive in a Poisson process at rate \lambda n, where \lambda >0 is a constant. Upon arrival, each ball chooses a fixed number d of random bins, and is placed into one with least load. Balls have…

Probability · Mathematics 2007-05-23 Malwina J. Luczak , Colin McDiarmid

In this paper, we consider a multi-drawing urn model with random addition. At each discrete time step, we draw a sample of m balls. According to the composition of the drawn colors, we return the balls together with a random number of balls…

Probability · Mathematics 2018-02-14 Rafik Aguech , Nabil Lasmar , Olfa Selmi

The random connection model is a random graph whose vertices are given by the points of a Poisson process and whose edges are obtained by randomly connecting pairs of Poisson points in a position dependent but independent way. We study…

Probability · Mathematics 2018-08-06 Günter Last , Franz Nestmann , Matthias Schulte

We investigate the typical cycle lengths, the total number of cycles, and the number of finite cycles in random permutations whose probability involves cycle weights. Typical cycle lengths and total number of cycles depend strongly on the…

Probability · Mathematics 2013-11-28 Nicholas M. Ercolani , Daniel Ueltschi

In this paper we study the component structure of random graphs with independence between the edges. Under mild assumptions, we determine whether there is a giant component, and find its asymptotic size when it exists. We assume that the…

Probability · Mathematics 2010-06-29 Bela Bollobas , Svante Janson , Oliver Riordan

We develop dependent hierarchical normalized random measures and apply them to dynamic topic modeling. The dependency arises via superposition, subsampling and point transition on the underlying Poisson processes of these measures. The…

Machine Learning · Computer Science 2012-06-22 Changyou Chen , Nan Ding , Wray Buntine

Systems of pinned billiard balls serve as simplified models of collisions, where all particles remain fixed in their positions while their (pseudo-)velocities evolve in accordance with the laws of conservation of energy and momentum. For…

We consider the Widom--Rowlinson model in which hard balls of two possible colors are constrained to a hard-core repulsion between particles of different colors, in quenched random environments. These random environments model spatially…

Probability · Mathematics 2026-04-27 Benedikt Jahnel , Christof Külske , Alexander Zass

Two approaches to incorporate heterogeneity in discrete models are compared. In the first, standard approach, the heterogeneity is dictated by geometrical structure of the discrete system. In the second approach, the heterogeneity is…

Computational Engineering, Finance, and Science · Computer Science 2025-06-26 Jan Raisinger , Qiwei Zhang , John E. Bolander , Jan Eliáš

We consider random rooted maps without regard to their genus, with fixed large number of edges, and address the problem of limiting distributions for six different parameters: vertices, leaves, loops, root edges, root isthmus, and root…

Combinatorics · Mathematics 2018-02-21 Olivier Bodini , Julien Courtiel , Sergey Dovgal , Hsien-Kuei Hwang

Consider a set of $n$ vertices, where each vertex has a location in $\mathbb{R}^d$ that is sampled uniformly from the unit cube in $\mathbb{R}^d$, and a weight associated to it. Construct a random graph by placing edges independently for…

Probability · Mathematics 2022-09-07 Remco van der Hofstad , Pim van der Hoorn , Neeladri Maitra