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Related papers: On the moment distance of Poisson processes

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In a discrete-time setting, we consider an arrival process $\left\{\xi_n \, \middle| \, n = 1, 2, \ldots \right\}$, which models the occurrence of events, and a corresponding point process $\left\{H_n \, \middle| \, n = 1, 2, \ldots…

Probability · Mathematics 2026-03-10 Utpal Jyoti Deba Sarma , Dharmaraja Selvamuthu

A determinantal point process is a stochastic point process that is commonly used to capture negative correlations. It has become increasingly popular in machine learning in recent years. Sampling a determinantal point process however…

Numerical Analysis · Mathematics 2020-09-02 Lexing Ying

We consider a random walk among i.i.d. obstacles on the one dimensional integer lattice under the condition that the walk starts from the origin and reaches a remote location y. The obstacles are represented by a killing potential, which…

Probability · Mathematics 2015-06-12 Elena Kosygina

We show that a stationary IDp process (i.e., an infinitely divisible stationary process without Gaussian part) can be written as the independent sum of four stationary IDp processes, each of them belonging to a different class characterized…

Probability · Mathematics 2011-11-10 Emmanuel Roy

We introduce a non-homogeneous fractional Poisson process by replacing the time variable in the fractional Poisson process of renewal type with an appropriate function of time. We characterize the resulting process by deriving its non-local…

Probability · Mathematics 2016-01-18 N. Leonenko , E. Scalas , M. Trinh

A Poisson line process is a random set of straight lines contained in the plane, as the image of the map $(x,v)\mapsto (x+vt)_{t\in\mathbb{R}}$, for each point $(x,v)$ of a Poisson process in the space-velocity plane. By associating a step…

Probability · Mathematics 2025-11-10 Pablo A. Ferrari , Stefano Olla

We propose a numerical method to approximate the value function for the optimal stopping problem of a piecewise deterministic Markov process (PDMP). Our approach is based on quantization of the post jump location---inter-arrival time Markov…

Probability · Mathematics 2016-08-14 Benoîte de Saporta , François Dufour , Karen Gonzalez

The Pitman-Yor process is a random discrete measure. The random weights or masses follow the two-parameter Poisson-Dirichlet distribution with parameters $0<\alpha<1, \theta>-\alpha$. The parameters $\alpha$ and $\theta$ correspond to the…

Probability · Mathematics 2016-02-29 Shui Feng , Fuqing Gao , Youzhou Zhou

We describe all countable particle systems on $\mathbb{R}$ which have the following three properties: independence, Gaussianity and stationarity. More precisely, we consider particles on the real line starting at the points of a Poisson…

Probability · Mathematics 2010-11-16 Zakhar Kabluchko

We present a simple derivation of a Feynman-Kac type formula to study fermionic systems. In this approach the real time or the imaginary time dynamics is expressed in terms of the evolution of a collection of Poisson processes. A computer…

Condensed Matter · Physics 2009-10-31 Matteo Beccaria , Carlo Presilla , Gian Fabrizio De Angelis , Giovanni Jona-Lasinio

Our purpose in this paper is to apply the general methodology for model selection based on T-estimators developed in Birg\'{e} [Ann. Inst. H. Poincar\'{e} Probab. Statist. 42 (2006) 273--325] to the particular situation of the estimation of…

Statistics Theory · Mathematics 2009-09-29 Lucien Birgé

We apply a discrete version of the methodology in \cite{gauss} to obtain a recursive asymptotic expansion for $\esp[h(W)]$ in terms of Poisson expectations, where $W$ is a sum of independent integer-valued random variables and $h$ is a…

Probability · Mathematics 2009-04-28 Ying Jiao

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

The distance covariance of two random vectors is a measure of their dependence. The empirical distance covariance and correlation can be used as statistical tools for testing whether two random vectors are independent. We propose an analogs…

Statistics Theory · Mathematics 2017-03-31 Muneya Matsui , Thomas Mikosch , Gennady Samorodnitsky

The Ulam distance of two permutations on $[n]$ is $n$ minus the length of their longest common subsequence. In this paper, we show that for every $\varepsilon>0$, there exists some $\alpha>0$, and an infinite set $\Gamma\subseteq…

Information Theory · Computer Science 2024-05-14 Elazar Goldenberg , Mursalin Habib , Karthik C. S

The persistence of a stochastic variable is the probability that it does not cross a given level during a fixed time interval. Although persistence is a simple concept to understand, it is in general hard to calculate. Here we consider zero…

Statistical Mechanics · Physics 2018-05-09 Markus Nyberg , Ludvig Lizana

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

Let $\eta_t$ be a Poisson point process with intensity measure $t\mu$, $t>0$, over a Borel space $\mathbb{X}$, where $\mu$ is a fixed measure. Another point process $\xi_t$ on the real line is constructed by applying a symmetric function…

Probability · Mathematics 2015-10-02 Matthias Schulte , Christoph Thaele

The Poisson process of order $i$ is a weighted sum of independent Poisson processes and is used to model the flow of clients in different services. In the paper below we study some extensions of this process, for different forms of the…

Probability · Mathematics 2019-10-01 A. Maheshwari , E. Orsingher , A. S. Sengar

In this article, we introduce Skellam process of order k and its running average. We also discuss the time-changed Skellam process of order k. In particular we discuss space-fractional Skellam process and tempered space-fractional Skellam…

Probability · Mathematics 2020-12-02 Neha Gupta , Arun Kumar , Nikolai Leonenko
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