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In this paper, a new natural discrete version of the one parameter polynomial exponential family of distributions have been proposed and studied. The distribution is named as Natural Discrete One Parameter Polynomial Exponential (NDOPPE)…

Statistics Theory · Mathematics 2020-07-08 Sudhansu S. Maiti , Molay Kumar Ruidas , Sumanta Adhya

In this paper, we give an alternative proof of the fact that, when compounding a nonnegative probability distribution, convex ordering between the distributions of the number of summands implies convex ordering between the resulting…

Probability · Mathematics 2019-10-17 Jean Bérard , Nicolas Juillet

Estimation of the operational risk capital under the Loss Distribution Approach requires evaluation of aggregate (compound) loss distributions which is one of the classic problems in risk theory. Closed-form solutions are not available for…

Computational Finance · Quantitative Finance 2014-09-23 Pavel V. Shevchenko

This paper introduces constrained mixtures for continuous distributions, characterized by a mixture of distributions where each distribution has a shape similar to the base distribution and disjoint domains. This new concept is used to…

Machine Learning · Statistics 2015-03-29 Conrado S. Miranda , Fernando J. Von Zuben

This paper proposes a generalisation of the Pearson type II distribution, which shall termed Pearson Type II-Riesz distribution, based in the Kotz-Riesz distribution. Specifically, the central nonsingular matricvariate generalised Pearson…

Statistics Theory · Mathematics 2015-06-17 Jose A. Diaz-Garcia , Francisco J. Caro-Lopera

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

The Poisson distribution arises naturally when dealing with data involving counts, and it has found many applications in inverse problems and imaging. In this work, we develop an approximate Bayesian inference technique based on expectation…

Numerical Analysis · Mathematics 2019-09-04 Chen Zhang , Simon Arridge , Bangti Jin

A compound Poisson process whose randomized time is an independent Poisson process is called compound Poisson process with Poisson subordinator. We provide its probability distribution, which is expressed in terms of the Bell polynomials,…

Probability · Mathematics 2015-11-18 Antonio Di Crescenzo , Barbara Martinucci , Shelemyahu Zacks

In distributionally robust optimization the probability distribution of the uncertain problem parameters is itself uncertain, and a fictitious adversary, e.g., nature, chooses the worst distribution from within a known ambiguity set. A…

Optimization and Control · Mathematics 2018-05-10 Etienne de Klerk , Daniel Kuhn , Krzysztof Postek

If a given aggregate process $S$ is a compound mixed Poisson process under a probability measure $P$, a characterization of all probability measures $Q$ on the domain of $P$, such that $P$ and $Q$ are progressively equivalent and $S$…

Probability · Mathematics 2019-05-21 Demetrios P. Lyberopoulos , Nikolaos D. Macheras

We show that for all $\psi$-mixing shifts distributions of the numbers of multiple recurrencies to shrinking cylindrical neighborhoods of all points are close either to Poisson or to compound Poisson distributions. We also describe…

Probability · Mathematics 2012-12-11 Yuri Kifer , Ariel Rapaport

This article concerns a class of generalized linear mixed models for clustered data, where the random effects are mapped uniquely onto the grouping structure and are independent between groups. We derive necessary and sufficient conditions…

Methodology · Statistics 2017-09-20 Jarod Y. L. Lee , Peter J. Green , Louise M. Ryan

This paper investigates the combinatorics that gives rise to the Boltzmann probability distribution. Despite being one of the most important distributions in physics and other fields of science, the mathematics of the underlying model of…

Probability · Mathematics 2025-07-09 Bart Jacobs

A tempered version of the discrete Linnik distribution is introduced in order to obtain integer-valued distribution families connected to stable laws. The proposal constitutes a generalization of the well-known Poisson-Tweedie law, which is…

Statistics Theory · Mathematics 2016-05-10 Lucio Barabesi , Carolina Becatti , Marzia Marcheselli

A new three parameter natural extension of the Conway-Maxwell-Poisson (COM-Poisson) distribution is proposed. This distribution includes the recently proposed COM-Poisson type negative binomial (COM-NB) distribution [Chakraborty, S. and…

Statistics Theory · Mathematics 2015-09-02 Subrata Chakraborty , Tomoaki Imoto

This note presents a rigorous introduction to a selection of distributions along with their Fourier transforms, which are commonly encountered in signal processing and, in particular, magnetic resonance imaging (MRI). In contrast to many…

Functional Analysis · Mathematics 2025-06-24 Kaibo Tang

We show that for planar dispersing billiards the return times distribution is, in the limit, Poisson for metric balls almost everywhere w.r.t. the SRB measure. Since the Poincar\'e return map is piecewise smooth but becomes singular at the…

Dynamical Systems · Mathematics 2014-11-10 Jorge Milhazes Freitas , Nicolai Haydn , Matthew Nicol

The binomial and Poisson distributions have interesting relationships with the beta and gamma distributions, respectively, which involve their cumulative distribution functions and the use of conjugate priors in Bayesian statistics. We…

Statistics Theory · Mathematics 2016-10-25 Peter Peskun

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

Statistical inference on the mean of a Poisson distribution is a fundamentally important problem with modern applications in, e.g., particle physics. The discreteness of the Poisson distribution makes this problem surprisingly challenging,…

Methodology · Statistics 2012-07-03 Ryan Martin , Duncan Ermini Leaf , Chuanhai Liu