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For a class of symplectic manifolds, we introduce a functional which assigns a real number to any pair of continuous functions on the manifold. This functional has a number of interesting properties. On the one hand, it is Lipschitz with…

Symplectic Geometry · Mathematics 2007-07-15 Michael Entov , Leonid Polterovich , Frol Zapolsky

The pair correlation function is a fundamental spatial point process characteristic that, given the intensity function, determines second order moments of the point process. Non-parametric estimation of the pair correlation function is a…

Statistics Theory · Mathematics 2023-04-25 Abdollah Jalilian , Yongtao Guan , Rasmus Waagepetersen

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

Excursion sets of Poisson shot noise processes are a prominent class of random sets. We consider a specific class of Poisson shot noise processes whose excursion sets within compact convex observation windows are almost surely polyconvex.…

Probability · Mathematics 2024-05-14 Vanessa Trapp

The problem of parameter estimation by i.i.d. observations of an inhomogeneous Poisson process is considered in situation of misspecification. The model is that of a Poissonian signal observed in presence of a homogeneous Poissonian noise.…

Statistics Theory · Mathematics 2022-11-21 O V Chernoyarov , S Dachian , Yu A Kutoyants

Classical peaks over threshold analysis is widely used for statistical modeling of sample extremes, and can be supplemented by a model for the sizes of clusters of exceedances. Under mild conditions a compound Poisson process model allows…

Applications · Statistics 2016-08-14 Mária Süveges , Anthony C. Davison

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

This paper deals with the union set of a stationary Poisson process of cylinders in $\mathbb{R}^n$ having an $(n-m)$-dimensional base and an $m$-dimensional direction space, where $m\in\{0,1,\ldots,n-1\}$ and $n\geq 2$. The concept…

Probability · Mathematics 2021-11-09 Carina Betken , Matthias Schulte , Christoph Thäle

We consider the moving particle process in Rd which is defined in the following way. There are two independent sequences (Tk) and (dk) of random variables. The variables Tk are non negative and form an increasing sequence, while variables…

Probability · Mathematics 2016-09-27 Youri Davydov , Valentin Konakov

This paper describes a new entropy-style of equation that may be useful in a general sense, but can be applied to a cognitive model with related processes. The model is based on the human brain, with automatic and distributed pattern…

Artificial Intelligence · Computer Science 2021-04-23 Kieran Greer

Consider a compound Poisson process with jump measure $\nu$ supported by finitely many positive integers. We propose a method for estimating $\nu$ from a single, equidistantly sampled trajectory and develop associated statistical…

Statistics Theory · Mathematics 2009-09-29 Werner Ehm , Benjamin Staude , Stefan Rotter

The representation theory of tensor functions is a powerful mathematical tool for constitutive modeling of anisotropic materials. A major limitation of the traditional theory is that many point groups require fourth- or sixth-order…

Representation Theory · Mathematics 2026-03-13 Mohammad Madadi , Pu Zhang

We use a functional analogue of the quantile function for probability measures on $\mathbb{R}^d$ to characterize a novel limit Poisson point process for radially recentred and rescaled random vectors under a radial-directional…

Methodology · Statistics 2025-01-31 Ioannis Papastathopoulos , Lambert de Monte , Ryan Campbell , Haavard Rue

This paper introduces a new modeling framework for the statistical analysis of point patterns on a manifold M_{d}, defined by a connected and compact two-point homogeneous space, including the special case of the sphere. The presented…

Methodology · Statistics 2022-10-21 M. P. Frías , A. Torres , M. D. Ruiz-Medina

We discuss a general Bayesian framework on modeling multidimensional function-valued processes by using a Gaussian process or a heavy-tailed process as a prior, enabling us to handle nonseparable and/or nonstationary covariance structure.…

Methodology · Statistics 2020-07-29 Evandro Konzen , Jian Qing Shi , Zhanfeng Wang

This chapter is an attempt to present a mathematical theory of compound fractional Poisson processes. The chapter begins with the characterization of a well-known L\'evy process: The compound Poisson process. The semi-Markov extension of…

Probability · Mathematics 2011-03-04 Enrico Scalas

Borisov, Mamaev and Kilin have recently found certain Poisson structures with respect to which the reduced and rescaled systems of certain non-holonomic problems, involving rolling bodies without slipping, become Hamiltonian, the…

Mathematical Physics · Physics 2007-05-23 Arturo Ramos

Let $M$ be an $n$-dimensional Hadamard manifold of pinched negative curvature $-b^2 \leq K_M \leq -a^2$. The solution of the Dirichlet problem at infinity for $M$ leads to the construction of a family of mutually absolutely continuous…

Differential Geometry · Mathematics 2024-08-13 Kingshook Biswas , Utsav Dewan , Arkajit Pal Choudhury

Using the Poisson bracket method, we derive continuum equations for a fluid of deformable particles in two dimensions. Particle shape is quantified in terms of two continuum fields: an anisotropy density field that captures the deformations…

Soft Condensed Matter · Physics 2021-04-07 Arthur Hernandez , M. Cristina Marchetti

Events in spatiotemporal domains arise in numerous real-world applications, where uncovering event relationships and enabling accurate prediction are central challenges. Classical Poisson and Hawkes processes rely on restrictive parametric…

Machine Learning · Computer Science 2026-03-26 Zhitong Xu , Qiwei Yuan , Yinghao Chen , Yan Sun , Bin Shen , Shandian Zhe
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