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We study sums of independent random variables that take values $0$, $1/2$, or $1$. We show that the probability mass function of the sum splits into two interleaved parts: one supported on the integers and the other supported on the…

Probability · Mathematics 2026-03-11 Mark Broadie , Ina Petkova

Given a statistical model, we propose a novel estimation method that yields randomised estimators for the unknown distribution of an observed random variable. We establish non-asymptotic bounds for the performance of these estimators and…

Statistics Theory · Mathematics 2026-05-06 Yannick Baraud

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

In a Cox model, the partial likelihood, as the product of a series of conditional probabilities, is used to estimate the regression coefficients. In practice, those conditional probabilities are approximated by risk score ratios based on a…

Methodology · Statistics 2025-02-27 Youngjin Cho , Yili Hong , Pang Du

We prove that certain natural random variables associated with the local eigenvalue statistics for generalized lattice Anderson models constructed with finite-rank perturbations are compound Poisson distributed. This distribution is…

Mathematical Physics · Physics 2015-09-30 Peter D. Hislop , M. Krishna

In probability theory, there is a tendency to treat one random variable with a given distribution as being just as good as any other. By and large this is fine because probability is (mostly) concerned with distributional properties of…

Probability · Mathematics 2013-01-31 Douglas Rizzolo

This paper proposes a generalized binomial distribution with four parameters, which is derived from the finite capacity queueing system with state-dependent service and arrival rates. This distribution is also generated from the conditional…

Statistics Theory · Mathematics 2016-10-18 Imoto Tomoaki , Ng Choung Min , Ong Seng Huat , Subrata Chakraborty

Let $X$ and $Y$ be independent variance-gamma random variables with zero location parameter; then the exact probability density function of the ratio $X/Y$ is derived. Some basic distributional properties are also derived, including…

Probability · Mathematics 2023-02-27 Robert E. Gaunt , Siqi Li

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

Sufficient conditions are developed, under which the compound Poisson distribution has maximal entropy within a natural class of probability measures on the nonnegative integers. Recently, one of the authors [O. Johnson, {\em Stoch. Proc.…

Combinatorics · Mathematics 2013-03-20 Oliver Johnson , Ioannis Kontoyiannis , Mokshay Madiman

This work defines and investigates the properties of the Max-U-Exp distribution. The method of moments is applied in order to estimate its parameters. Then, by using the previous general theory about Mixed Poisson processes, developed by…

Probability · Mathematics 2024-02-15 Pavlina K. Jordanova , Evelina Veleva

A novel approach to parton distributions parameterization in terms of quantum statistical functions is here outlined. The description, already proposed in previous publications, is here improved by adding to the statistical distributions an…

High Energy Physics - Phenomenology · Physics 2007-05-23 G. Miele

The exact expression for the probability density $p_{_N}(x)$ for sums of a finite number $N$ of random independent terms is obtained. It is shown that the very tail of $p_{_N}(x)$ has a Gaussian form if and only if all the random terms are…

Probability · Mathematics 2013-05-29 Michael I. Tribelsky

It will be recalled that the classical bivariate normal distributions have normal marginals and normal conditionals. It is natural to ask whether a similar phenomenon can be encountered involving Poisson marginals and conditionals.…

Methodology · Statistics 2020-09-04 Barry C. Arnold , B. G. Manjunath

We show that a slight modification of a theorem of Ruzmaikina and Aizenman on competing particle systems on the real line leads to a characterization of Poisson-Dirichlet distributions $PD(a,0)$. Precisely, let $s$ be a proper random…

Probability · Mathematics 2010-11-09 Louis-Pierre Arguin

We prove a long-standing conjecture which characterises the Ewens-Pitman two-parameter family of exchangeable random partitions, plus a short list of limit and exceptional cases, by the following property: for each $n = 2,3, >...$, if one…

Probability · Mathematics 2009-11-20 Alexander Gnedin , Chris Haulk , Jim Pitman

This article brings in two new discrete distributions: multidimensional Binomial distribution and multidimensional Poisson distribution. Those distributions were created in eventology as more correct generalizations of Binomial and Poisson…

General Mathematics · Mathematics 2011-02-23 Oleg Yu. Vorobyev , Lavrentiy S. Golovkov

We consider two types of entropy, namely, Shannon and R\'{e}nyi entropies of the Poisson distribution, and establish their properties as the functions of intensity parameter. More precisely, we prove that both entropies increase with…

Information Theory · Computer Science 2024-03-15 Volodymyr Braiman , Anatoliy Malyarenko , Yuliya Mishura , Yevheniia Anastasiia Rudyk

In this paper, an alternative mixed Poisson distribution is proposed by amalgamating Poisson distribution and a modification of the Quasi Lindley distribution. Some fundamental structural properties of the new distribution, namely the shape…

Methodology · Statistics 2021-10-26 Ramajeyam Tharshan , Pushpakanthie Wijekoon

Let $X_1,\ldots,X_M$ and $Y_1,\ldots,Y_N$ be independent zero mean normal random variables with variances $\sigma_{X_i}^2$, $i=1,\ldots,M$, and $\sigma_{Y_j}^2$, $j=1,\ldots,N$, respectively, and let $X=X_1\cdots X_M$ and $Y=Y_1\cdots Y_N$.…

Probability · Mathematics 2026-01-21 Robert E. Gaunt , Heather L. Sutcliffe
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