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We approximate the distribution of the sum of independent but not necessarily identically distributed Bernoulli random variables using a shifted binomial distribution where the three parameters (the number of trials, the probability of…

Probability · Mathematics 2010-04-02 Vydas Čekanavičius , Erol A. Peköz , Adrian Röllin , Michael Shwartz

The Poisson distribution is the default choice of likelihood for probabilistic models of count data. However, due to the equidispersion contraint of the Poisson, such models may have predictive uncertainty that is artificially inflated.…

Methodology · Statistics 2025-07-15 Jimmy Lederman , Aaron Schein

Azzalini & Dalla Valle (1996) have recently discussed the multivariate skew-normal distribution which extends the class of normal distributions by the addition of a shape parameter. The first part of the present paper examines further…

Methodology · Statistics 2009-11-12 Adelchi Azzalini , Antonella Capitanio

A random variable is equi-dispersed if its mean equals its variance. A Poisson distribution is a classical example of this phenomenon. However, a less well-known fact is that the class of normal densities that are equi-dispersed constitutes…

Statistics Theory · Mathematics 2022-09-07 Barry C. Arnold , B. G. Manjunath

We consider Kemp's q-analogue of the binomial distribution. Several convergence results involving the classical binomial, the Heine, the discrete normal, and the Poisson distribution are established. Some of them are q-analogues of…

Probability · Mathematics 2008-04-04 Stefan Gerhold , Martin Zeiner

We propose an algorithm for evaluation of the cumulative bivariate normal distribution, building upon Marsaglia's ideas for evaluation of the cumulative univariate normal distribution. The algorithm is mathematically transparent, delivers…

Numerical Analysis · Mathematics 2018-09-19 Christian Meyer

Convolutions of independent random variables often arise in a natural way in many applied problems. In this article, we compare convolutions of two sets of gamma (negative binomial) random variables in the convolution order and the usual…

Probability · Mathematics 2018-11-29 Ying Zhang

A generalization of a distribution increases the flexibility particularly in studying of a phenomenon and its properties. Many generalizations of continuous univariate distributions are available in literature. In this study, an…

Applications · Statistics 2024-08-30 Brijesh P. Singh , Sandeep Singh , Utpal Dhar Das

A continuous approximation for the results of [1] is obtained. In this approximation the energy distribution is represented in the form of the product of the Gibbs factor and superstatistics factor. The mutual weights of the factors are…

Chemical Physics · Physics 2007-05-23 V. V. Ryazanov

It is well-known that the Shannon entropies of some parameterized probability distributions are concave functions with respect to the parameter. In this paper we consider a family of such distributions (including the binomial, Poisson, and…

Classical Analysis and ODEs · Mathematics 2016-08-19 Ioan Rasa

A new discrete distribution has been proposed as a discrete analogue of the two sided power distribution [Van Drop, J. R. and Kotz, S. (2002a). A novel extension of the triangular distribution and its parameter estimation, Journal of the…

Statistics Theory · Mathematics 2015-01-27 Subrata Chakraborty , Dhrubajyoti Chakravarty

We develop a general method for computing logarithmic and log-gamma expectations of distributions. As a result, we derive series expansions and integral representations of the entropy for several fundamental distributions, including the…

Information Theory · Computer Science 2018-07-24 Mahdi Cheraghchi

We consider a basic problem in unsupervised learning: learning an unknown \emph{Poisson Binomial Distribution}. A Poisson Binomial Distribution (PBD) over $\{0,1,\dots,n\}$ is the distribution of a sum of $n$ independent Bernoulli random…

Data Structures and Algorithms · Computer Science 2015-02-18 Constantinos Daskalakis , Ilias Diakonikolas , Rocco A. Servedio

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

We develop a new class of dynamic multivariate Poisson count models that allow for fast online updating and we refer to these models as multivariate Poisson-scaled beta (MPSB). The MPSB model allows for serial dependence in the counts as…

Methodology · Statistics 2016-09-16 Tevfik Aktekin , Nicholas G. Polson , Refik Soyer

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

A new fractional non-homogeneous counting process has been introduced and developed using the Kilbas and Saigo three-parameter generalization of the Mittag-Leffler function. The probability distribution function of this process reproduces…

Probability · Mathematics 2024-01-01 Nick Laskin

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

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

We consider a generalised diffusion equation in two dimensions for modeling diffusion on a comb-like structures. We analyse the probability distribution functions and we derive the mean squared displacement in $x$ and $y$ directions.…

Statistical Mechanics · Physics 2016-06-23 Trifce Sandev , Alexander Iomin , Holger Kantz , Ralf Metzler , Aleksei Chechkin