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Dynamical scaling is an asymptotic property typical for the dynamics of first-order phase transitions in physical systems and related to self-similarity. Based on the integral-representation for the marginal probabilities of a fractional…

Probability · Mathematics 2021-07-23 Markus Kreer

The paper considers a Cox process where the stochastic intensity function for the Poisson data model is itself a non-homogeneous Poisson process. We show that it is possible to obtain the marginal data process, namely a non-homogeneous…

Methodology · Statistics 2023-04-17 Shuying Wang , Stephen G. Walker

Dunkl processes are martingales as well as c\`{a}dl\`{a}g homogeneous Markov processes taking values in $\mathbb{R}^d$ and they are naturally associated with a root system. In this paper we study the jumps of these processes, we describe…

Probability · Mathematics 2016-08-16 Léonard Gallardo , Marc Yor

Representations of branching Markov processes and their measure-valued limits in terms of countable systems of particles are constructed for models with spatially varying birth and death rates. Each particle has a location and a "level,"…

Probability · Mathematics 2011-04-11 Thomas G. Kurtz , Eliane R. Rodrigues

Define the scaled empirical point process on an independent and identically distributed sequence $\{Y_i: i\le n\}$ as the random point measure with masses at $a_n^{-1} Y_i$. For suitable $a_n$ we obtain the weak limit of these point…

Probability · Mathematics 2016-08-16 André Dabrowski , Gail Ivanoof , Rafal Kulik

Let $\tilde{N}\_{t}$ be a standard compensated Poisson process on $[0,1]$. We prove a new characterization of anticipating integrals of the Skorohod type with respect to $\tilde{N}$, and use it to obtain several counterparts to well…

Probability · Mathematics 2007-05-23 Giovanni Peccati , Ciprian A. Tudor

The binomial, the negative binomial, the Poisson, the compound Poisson and the Erlang distribution do all admit integral representations with respect to its (continuous) parameter. We use the Margulis-Russo type formulas for Bernoulli and…

Probability · Mathematics 2026-02-05 Guenter Last , Sergei Zuyev

We consider the sequential sampling of species, where observed samples are classified into the species they belong to. We are particularly interested in studying some quantities describing the sampling process when there is a new species…

Probability · Mathematics 2023-02-01 Servet Martínez , Javier Santibáñez

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 work, based on a realization of an inhomogeneous Poisson process whose intensity function depends on a real unknown parameter, we consider a simple hypothesis against a sequence of close (contiguous) alternatives. Under certain…

Statistics Theory · Mathematics 2007-07-02 Khosrow Fazli

In the present paper we demonstrate the results of a statistical analysis of some characteristics of precipitation events and propose a kind of a theoretical explanation of the proposed models in terms of mixed Poisson and mixed exponential…

Probability · Mathematics 2018-06-28 V. Yu. Korolev , A. K. Gorshenin , S. K. Gulev , K. P. Belyaev , A. A. Grusho

The paper deals with disorders detection in the multivariate stochastic process. We consider the multidimensional Poisson process or the multivariate renewal process. This class of processes can be used as a description of the distributed…

Optimization and Control · Mathematics 2021-01-12 Krzysztof J. Szajowski

In the series of models with interacting particles in stochastic geometry, a new contribution presents the facet process which is defined in arbitrary Euclidean dimension. In 2D, 3D specially it is a process of interacting segments, flat…

Probability · Mathematics 2015-04-02 Jakub Vecera , Viktor Benes

Data on count processes arise in a variety of applications, including longitudinal, spatial and imaging studies measuring count responses. The literature on statistical models for dependent count data is dominated by models built from…

Methodology · Statistics 2013-10-08 Antonio Canale , David B. Dunson

This paper addresses the mapping problem. Using a conjugate prior form, we derive the exact theoretical batch multi-object posterior density of the map given a set of measurements. The landmarks in the map are modeled as extended objects,…

Machine Learning · Statistics 2018-11-09 Maryam Fatemi , Karl Granström , Lennart Svensson , Francisco J. R. Ruiz , Lars Hammarstrand

This paper studies the joint moments of a compound discounted renewal process observed at different times with each arrival removed from the system after a random delay. This process can be used to describe the aggregate (discounted)…

Probability · Mathematics 2018-12-10 Eric Cheung , Landy Rabehasaina , Jae-Kyung Woo , Ran Xu

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

A multivariate fractional Poisson process was recently defined in Beghin and Macci (2016) by considering a common independent random time change for a finite dimensional vector of independent (non-fractional) Poisson processes; moreover it…

Probability · Mathematics 2016-09-13 Luisa Beghin , Claudio Macci

In [Schuhmacher, Electron. J. Probab. 10 (2005), 165--201] estimates of the Barbour-Brown distance d_2 between the distribution of a thinned point process and the distribution of a Poisson process were derived by combining discretization…

Probability · Mathematics 2007-05-23 Dominic Schuhmacher

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