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In this paper, a Bayesian method for piecewise regression is adapted to handle counting processes data distributed as Poisson. A numerical code in Mathematica is developed and tested analyzing simulated data. The resulting method is…

Data Analysis, Statistics and Probability · Physics 2017-02-21 Diego Sevilla

We analyze here different types of fractional differential equations, under the assumption that their fractional order $\nu \in (0,1] $ is random\ with probability density $n(\nu).$ We start by considering the fractional extension of the…

Probability · Mathematics 2015-05-27 Luisa Beghin

Consider two independent Poisson point processes of unit intensity in the Euclidean space of dimension $d$ at least 3. We construct a perfect matching between the two point sets that is a factor (i.e., an equivariant measurable function of…

Probability · Mathematics 2025-02-14 Adam Timar

A novel over-dispersed discrete distribution, namely the PoiTG distribution is derived by the convolution of a Poisson variate and an independently distributed transmuted geometric random variable. This distribution generalizes the…

Statistics Theory · Mathematics 2024-08-02 Anupama Nandi , Subrata Chakraborty , Aniket Biswas

An information-theoretic development is given for the problem of compound Poisson approximation, which parallels earlier treatments for Gaussian and Poisson approximation. Let $P_{S_n}$ be the distribution of a sum $S_n=\Sumn Y_i$ of…

Probability · Mathematics 2019-06-05 A. D. Barbour , Oliver Johnson , Ioannis Kontoyiannis , Mokshay Madiman

This article provides some characterizations of extended COM-Poisson distribution: conditional distribution given the sum, functional operator characterization (Stein identity). We also give some conditions such that the extended…

Statistics Theory · Mathematics 2015-08-26 Huiming Zhang

Doubly stochastic Poisson processes, also known as the Cox processes, frequently occur in various scientific fields. In this article, motivated primarily by analyzing Cox process data in biophysics, we propose a nonparametric kernel-based…

Applications · Statistics 2011-01-07 Tingting Zhang , S. C. Kou

The (conditional or unconditional) distribution of the continuous scan statistic in a one-dimensional Poisson process may be approximated by that of a discrete analogue via time discretization (to be referred to as the discrete…

Probability · Mathematics 2016-02-09 Yi-Ching Yao , Daniel Wei-Chung Miao , Xenos Chang-Shuo Lin

Fractional equations have become the model of choice in several applications where heterogeneities at the microstructure result in anomalous diffusive behavior at the macroscale. In this work we introduce a new fractional operator…

Numerical Analysis · Mathematics 2021-01-29 Marta D'Elia , Christian Glusa

Suppose that a compound Poisson process is observed discretely in time and assume that its jump distribution is supported on the set of natural numbers. In this paper we propose a non-parametric Bayesian approach to estimate the intensity…

Statistics Theory · Mathematics 2020-05-21 Shota Gugushvili , Ester Mariucci , Frank van der Meulen

In this paper the generalization of the Poisson distribution is derived for the case when each consecutive event changes event rate. A simple formula for the probability of observing of a given number of events for the selected period of…

Data Analysis, Statistics and Probability · Physics 2014-01-06 E. A. Kushnirenko

We consider the approximation of a convolution of possibly different probability measures by (compound) Poisson distributions and also by related signed measures of higher order. We present new total variation bounds having a better…

Probability · Mathematics 2017-03-08 Bero Roos

We consider the distribution of spacings between consecutive elements in subsets of Z/qZ where q is highly composite and the subsets are defined via the Chinese remainder theorem. We give a sufficient criterion for the spacing distribution…

Number Theory · Mathematics 2007-05-23 A. Granville , P. Kurlberg

The problem of parameter estimation by observations of inhomogeneous Poisson processes is considered. The method of moments estimator is studied and its stochastic expansion is obtained. This stochastic expansion is then used to obtain the…

Statistics Theory · Mathematics 2020-10-16 O. V. Chernoyarov , A. S. Dabye , F. N. Diop , Yu. A. Kutoyants

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…

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

A discrete-time stochastic process derived from a model of basketball is used to generalize any discrete distribution. The generalized distributions can have one or two more parameters than the parent distribution. Those derived from…

Applications · Statistics 2020-06-25 Rose Baker

The aim of this paper is to analyze a class of random motions which models the motion of a particle on the real line with random velocity and subject to the action of the friction. The speed randomly changes when a Poissonian event occurs.…

Probability · Mathematics 2009-12-31 Alessandro De Gregorio

This paper presents a new derivation of the Generalized Poisson distribution. This distribution provides a good fit to the evolved, counts-in-cells distribution measured in numerical simulations of hierarchical clustering from Poisson…

Astrophysics · Physics 2009-10-30 Ravi K. Sheth

This paper introduces a variable-order stable subordinator (VOSS) $S^{\alpha(t)}(t)$ with index $\alpha(t)\in(0,1)$, where $\alpha(t)$ is a right-continuous piecewise constant function. We drive the Generalized Space-Fractional Poisson…

Probability · Mathematics 2026-01-13 Reetendra Singh , Aditya Maheshwari