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In this paper, we introduce a new approach to generate flexible parametric families of distributions. These models arise on competitive and complementary risks scenario, in which the lifetime associated with a particular risk is not…

Applications · Statistics 2018-05-22 Pedro L. Ramos , Dipak K. Dey , Francisco Louzada , Victor H. Lachos

An important functional of Poisson random measure is the negative binomial process (NBP). We use NBP to introduce a generalized Poisson-Kingman distribution and its corresponding random discrete probability measure. This random discrete…

Statistics Theory · Mathematics 2023-07-04 Sadegh Chegini , Mahmoud Zarepour

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

In this article we survey properties of mixed Poisson distributions and probabilistic aspects of the Stirling transform: given a non-negative random variable $X$ with moment sequence $(\mu_s)_{s\in\mathbb{N}}$ we determine a discrete random…

Combinatorics · Mathematics 2014-09-12 Markus Kuba , Alois Panholzer

The insurance model when the amount of claims depends on the state of the insured person (healthy, ill, or dead) and claims are connected in a Markov chain is investigated. The signed compound Poisson approximation is applied to the…

Probability · Mathematics 2020-01-13 Gabija Liaudanskaitė , Vydas Čekanavičius

We generalize the Poisson limit theorem to binary functions of random objects whose law is invariant under the action of an amenable group. Examples include stationary random fields, exchangeable sequences, and exchangeable graphs. A…

Probability · Mathematics 2024-01-19 Haoyu Ye , Peter Orbanz , Morgane Austern

We consider a risk model with a counting process whose intensity is a Markovian shot-noise process, to resolve one of the disadvantages of the Cram\'er-Lundberg model, namely the constant jump intensity of the Poisson process. Due to this…

Probability · Mathematics 2022-05-11 Simon Pojer , Stefan Thonhauser

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

Let X be a Poisson point process of intensity lambda on the real line. A thickening of it is a (deterministic) measurable function f such that the union of X and f(X) is a Poisson point process of intensity lambda' where lambda'>lambda. An…

Probability · Mathematics 2017-03-14 Ori Gurel-Gurevich , Ron Peled

We study different fractional extensions of the Poisson process and generalized counting processes by introducing time-change represented by the inverse to the sums of stable and tempered stable subordinators. We state the governing…

Probability · Mathematics 2026-04-02 Lyudmyla Sakhno , Artem Storozhuk

Poisson shot noise processes are natural generalizations of compound Poisson processes that have been widely applied in insurance, neuroscience, seismology, computer science and epidemiology. In this paper we study sharp deviations,…

Probability · Mathematics 2021-08-12 Giovanni Luca Torrisi , Emilio Leonardi

In this article, the compound Poisson processes of order $k$ (CPPoK) is introduced and its properties are discussed. Further, using mixture of tempered stable subordinator (MTSS) and its right continuous inverse, the two subordinated CPPoK…

Probability · Mathematics 2020-05-05 Ayushi Singh Sengar , N. S. Upadhye

This paper introduces a new stochastic process with values in the set Z of integers with sign. The increments of process are Poisson differences and the dynamics has an autoregressive structure. We study the properties of the process and…

Methodology · Statistics 2020-02-12 Giulia Carallo , Roberto Casarin , Christian P. Robert

We construct a general stochastic process and prove weak convergence results. It is scaled in space and through the parameters of its distribution. We show that our simplified scaling is equivalent to time scaling used frequently. The…

Probability · Mathematics 2011-07-01 Mine Caglar

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 establish Poisson and compound Poisson approximations for stabilizing statistics of $\beta$-mixing point processes and give explicit rates of convergence. Our findings are based on a general estimate of the total variation distance of a…

Probability · Mathematics 2023-10-24 Nicolas Chenavier , Moritz Otto

We present the first fully variational Bayesian inference scheme for continuous Gaussian-process-modulated Poisson processes. Such point processes are used in a variety of domains, including neuroscience, geo-statistics and astronomy, but…

Machine Learning · Statistics 2015-07-29 Chris Lloyd , Tom Gunter , Michael A. Osborne , Stephen J. Roberts

We consider a general piecewise deterministic Markov process (PDMP) $X=\{X_t\}_{t\geqslant 0}$ with measure-valued generator $\mathcal{A}$, for which the conditional distribution function of the inter-occurrence time is not necessarily…

Probability · Mathematics 2017-04-27 Zhaoyang Liu , Yuying Liu , Guoxin Liu

We consider a weighted sum of a series of independent Poisson random variables and show that it results in a new compound Poisson distribution which includes the Poisson distribution and Poisson distribution of order k. An explicit…

Probability · Mathematics 2025-06-18 Palaniappan Vellaisamy , Tomoyuki Ichiba

We consider a class of semi-Markov processes (SMP) such that the embedded discrete time Markov chain may be non-homogeneous. The corresponding augmented processes are represented as semi-martingales using stochastic integral equation…

Probability · Mathematics 2022-07-14 Anindya Goswami , Subhamay Saha , Ravishankar Kapildev Yadav
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