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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

A random phenomenon may have two sources of random variation: an unstable identity and a set of external variation-generating factors. When only a single source is active, two mutually exclusive extreme scenarios may ensue that result in…

Statistics Theory · Mathematics 2015-07-28 Haim Shore

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

In this article, we discuss a bivariate distribution whose conditionals are univariate binomial distributions and the marginals are not binomial that exhibits negative correlation. Some useful structural properties of this distribution…

Methodology · Statistics 2023-01-10 Indranil Ghosh , Filipe Marques , Subrata Chakraborty

We consider three new classes of exponential dispersion models of discrete probability distributions which are defined by specifying their variance functions in their mean value parameterization. In a previous paper (Bar-Lev and Ridder,…

Methodology · Statistics 2020-04-01 Shaul K. Bar-Lev , Ad Ridder

The Poisson distribution has been widely studied and used for modeling univariate count-valued data. Multivariate generalizations of the Poisson distribution that permit dependencies, however, have been far less popular. Yet, real-world…

Methodology · Statistics 2016-12-28 David I. Inouye , Eunho Yang , Genevera I. Allen , Pradeep Ravikumar

Parametric distributions are an important part of statistics. There is now a voluminous literature on different fascinating formulations of flexible distributions. We present a selective and brief overview of a small subset of these…

Statistics Theory · Mathematics 2020-05-15 Sharon X. Lee , Geoffrey J. McLachlan

A discrete-time stochastic process derived from a model of basketball is used to generalize any discrete distribution. The generalized distributions can have one or two more parameters than the parent distribution. Those derived from…

Applications · Statistics 2020-06-25 Rose Baker

The (general) hypoexponential distribution is the distribution of a sum of independent exponential random variables. We consider the particular case when the involved exponential variables have distinct rate parameters. We prove that the…

Probability · Mathematics 2020-12-16 George P. Yanev

The sum of independent, but not necessary identically distributed, exponential random variables follows hypoexponential distribution. We focus on a particular case when all, but one rate parameters of the exponential variables are…

Probability · Mathematics 2023-04-04 George Yanev

Bivariate count data arise in several different disciplines (epidemiology, marketing, sports statistics, etc., to name but a few) and the bivariate Poisson distribution which is a generalization of the Poisson distribution plays an…

Methodology · Statistics 2023-01-12 Barry C. Arnold , Indranil Ghosh

In this paper, we introduce a new class of bivariate distributions by compounding the bivariate generalized exponential and power-series distributions. This new class contains some new sub-models such as the bivariate generalized…

Computation · Statistics 2015-08-04 Ali Akbar Jafari , Rasool Roozegar

In the analysis of count data often the equidispersion assumption is not suitable, hence the Poisson regression model is inappropriate. As a generalization of the Poisson distribution, the COM-Poisson distribution can deal with under-,…

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

Within the framework of probability models for overdispersed count data, we propose the generalized fractional Poisson distribution (gfPd), which is a natural generalization of the fractional Poisson distribution (fPd), and the standard…

Probability · Mathematics 2021-01-12 Dexter Cahoy , Elvira Di Nardo , Federico Polito

Marshall and Olkin (1997, Biometrika, 84, 641 - 652) introduced a very powerful method to introduce an additional parameter to a class of continuous distribution functions and hence it brings more flexibility to the model. They have…

Methodology · Statistics 2018-02-20 Debasis Kundu , Vahid Nekoukhou

This paper develops some objective priors for certain parameters of the bivariate normal distribution. The parameters considered are the regression coefficient, the generalized variance, and the ratio of the conditional variance of one…

Statistics Theory · Mathematics 2008-12-18 Malay Ghosh , Upasana Santra , Dalho Kim

We show that the Conway--Maxwell--Poisson distribution can be arbitrarily underdispersed when parametrized via its mean. More precisely, if the mean $\mu$ is an integer then the limiting distribution is a unit probability mass at $\mu$. If…

Statistics Theory · Mathematics 2020-11-17 Alan Huang

This paper introduces Schur-constant equilibrium distribution models of dimension n for arithmetic non-negative random variables. Such a model is defined through the (several orders) equilibrium distributions of a univariate survival…

Probability · Mathematics 2017-09-29 Anna Castañer , M Mercè Claramunt

A new two-parameter discrete distribution, namely the PoiG distribution is derived by the convolution of a Poisson variate and an independently distributed geometric random variable. This distribution generalizes both the Poisson and…

Methodology · Statistics 2024-07-11 Anupama Nandi , Subrata Chakraborty , Aniket Biswas
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