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The present paper considers modified extension of the exponential distribution with three parameters. We study the main properties of this new distribution, with special emphasis on its median, mode and moments function and some…

Other Statistics · Statistics 2015-10-28 M. A. El-Damcese , Dina. A. Ramadan

A new generalization of the family of Poisson-G is called beta Poisson-G family of distribution. Useful expansions of the probability density function and the cumulative distribution function of the proposed family are derived and seen as…

Statistics Theory · Mathematics 2020-05-22 Laba Handique , Subrata Chakraborty , Farrukh Jamal

In this paper, we propose a new class of distributions by exponentiating the random variables associated with the probability density functions of composite distributions. We also derive some mathematical properties of this new class of…

Methodology · Statistics 2022-04-05 Bowen Liu , Malwane M. A. Ananda

This paper introduces a discrete-time fractional Poisson process defined as a renewal process, where the waiting times follow a discrete Mittag-Leffler distribution. We investigate its fundamental properties by explicitly deriving the…

Probability · Mathematics 2026-05-06 Naohiro Yoshida

This paper deals with Poisson processes on an arbitrary measurable space. Using a direct approach, we derive formulae for moments and cumulants of a vector of multiple Wiener-It\^o integrals with respect to the compensated Poisson process.…

Probability · Mathematics 2014-07-08 Guenter Last , Mathew D. Penrose , Matthias Schulte , Christoph Thaele

In this paper the class of mixed renewal processes (MRPs for short) with mixing parameter a random vector from \cite{lm6z3} (enlarging Huang's \cite{hu} original class) is replaced by the strictly more comprising class of all extended MRPs…

Probability · Mathematics 2016-07-20 N. D. Macheras , S. M. Tzaninis

Although the specification of bivariate probability models using a collection of assumed conditional distributions is not a novel concept, it has received considerable attention in the last decade. In this study, a bivariate…

Methodology · Statistics 2025-03-20 Indranil Ghosh , Mina Norouzirad , Filipe J. Marques

Under mild assumptions the equivalence of the mixed Poisson process with mixing parameter a real-valued random variable to the one with mixing distribution as well as to the mixed Poisson process in the sense of Huang is obtained, and a…

Probability · Mathematics 2016-07-20 D. P. Lyberopoulos , N. D. Macheras , S. M. Tzaninis

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

A simple explicit construction is provided of a partition-valued fragmentation process whose distribution on partitions of $[n]=\{1,...,n\}$ at time $\theta \ge 0$ is governed by the Ewens sampling formula with parameter $\theta$. These…

Probability · Mathematics 2007-05-23 Alexander Gnedin , Jim Pitman

Filtered Poisson processes are often used as reference models for intermittent fluc- tuations in physical systems. Such a process is here extended by adding a noise term, either as a purely additive term to the process or as a dynamical…

Data Analysis, Statistics and Probability · Physics 2018-05-04 Audun Theodorsen , Odd Erik Garcia , Martin Rypdal

The empirical probability density function for the conditional distribution of the true value of Poisson distribution parameter on one measurement is constructed by computer experiment. The analysis of the obtained distributions confirms…

Data Analysis, Statistics and Probability · Physics 2009-11-10 S. I. Bityukov , V. A. Medvedev , V. V. Smirnova , Yu. V. Zernii

Statistical modeling of multivariate and spatial extreme events has attracted broad attention in various areas of science. Max-stable distributions and processes are the natural class of models for this purpose, and many parametric families…

Methodology · Statistics 2017-08-09 Clement Dombry , Sebastian Engelke , Marco Oesting

Many processes in chemistry and physics take place on timescales that cannot be explored using standard molecular dynamics simulations. This renders the use of enhanced sampling mandatory. Here we introduce an enhanced sampling method that…

Chemical Physics · Physics 2020-06-12 Jayashrita Debnath , Michele Parrinello

Through viewing out the literature, many generated distributions took a new special form of probability density function (PDF) in which it is written as a linear combination of n other distributions. Therefore, we define in this paper a new…

Statistics Theory · Mathematics 2022-11-15 Therar Kadri , Amina Halat

Carlitz [2] initiated a study on degenerate versions of Bernoulli and Euler numbers which has been extended recently to the researches on various degenerate versions of quite a few special numbers and polynomials. They have been explored by…

Number Theory · Mathematics 2021-06-28 Taekyun Kim , Dae san Kim , Hyunseok Lee , Seong Ho Park , Jongkyum Kwon

This paper is devoted to the prediction problem in extreme value theory. Our main result is an explicit expression of the regular conditional distribution of a max-stable (or max-infinitely divisible) process $\{\eta(t)\}_{t\in T}$ given…

Probability · Mathematics 2012-05-15 Clément Dombry , Frédéric Eyi-Minko

U-statistics of spatial point processes given by a density with respect to a Poisson process are investigated. In the first half of the paper general relations are derived for the moments of the functionals using kernels from the Wiener-Ito…

Probability · Mathematics 2014-06-24 Viktor Benes , Marketa Zikmundova

Counting experiments often rely on Monte Carlo simulations for predictions of Poisson expectations. The accompanying uncertainty from the finite Monte Carlo sample size can be incorporated into parameter estimation by modifying the Poisson…

Instrumentation and Methods for Astrophysics · Physics 2020-04-22 Thorsten Glüsenkamp

We develop a prior probability model for temporal Poisson process intensities through structured mixtures of Erlang densities with common scale parameter, mixing on the integer shape parameters. The mixture weights are constructed through…

Methodology · Statistics 2021-10-26 Hyotae Kim , Athanasios Kottas