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Related papers: Multivariate $\alpha$-normal distributions

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The lognormal distribution describing, e.g., exponentials of Gaussian random variables is one of the most common statistical distributions in physics. It can exhibit features of broad distributions that imply qualitative departure from the…

Data Analysis, Statistics and Probability · Physics 2009-11-07 M. Romeo , V. Da Costa , F. Bardou

The Tsallis $q$-Gaussian distribution is a powerful generalization of the standard Gaussian distribution and is commonly used in various fields, including non-extensive statistical mechanics, financial markets and image processing. It…

Computation · Statistics 2023-05-19 Viktor Witkovský

We introduce the beta generalized exponential distribution that includes the beta exponential and generalized exponential distributions as special cases. We provide a comprehensive mathematical treatment of this distribution. We derive the…

Methodology · Statistics 2010-08-17 Wagner Barreto-Souza , Alessandro H. S. Santos , Gauss M. Cordeiro

In this paper we study a broad class of distribution functions which is defined by means of reflected generalized beta distribution. This class includes that of Beta-generated distribution as a special case. In particular, we use this class…

Statistics Theory · Mathematics 2016-07-20 Ibrahim Elbatal , Francesca Condino , Filippo Domma

We study the Euler-Frobenius numbers, a generalization of the Eulerian numbers, and the probability distribution obtained by normalizing them. This distribution can be obtained by rounding a sum of independent uniform random variables; this…

Probability · Mathematics 2013-05-17 Svante Janson

Over the last two decades, it has been argued that the Lorentz transformation mechanism, which imposes the generalization of Newton's classical mechanics into Einstein's special relativity, implies a generalization, or deformation, of the…

Statistics Theory · Mathematics 2022-03-04 G. Kaniadakis

We express generalized Cauchy-Stieltjes transforms of some particular Beta distributions (of ultraspherical type generating functions for orthogonal polynomials) as a powered Cauchy-Stieltjes transform of some measure. For suitable values…

Probability · Mathematics 2009-02-03 Nizar Demni

In this work, we investigate how to develop sharp concentration inequalities for sub-Weibull random variables, including sub-Gaussian and sub-exponential distributions. Although the random variables may not be sub-Guassian, the tail…

Statistics Theory · Mathematics 2026-03-30 Yinan Shen , Jinchi Lv

To know the statistical distribution of a variable is an important problem in management of resources. Distributions of the power law type are observed in many real systems. However power law distributions have an infinite variance and thus…

Statistical Mechanics · Physics 2008-12-02 Hari M. Gupta , Jose R. Campanha

The Conway-Maxwell-Poisson distribution is a two-parameter generalisation of the Poisson distribution that can be used to model data that is under- or over-dispersed relative to the Poisson distribution. The normalizing constant…

Statistics Theory · Mathematics 2019-04-05 Robert E. Gaunt , Satish Iyengar , Adri B. Olde Daalhuis , Burcin Simsek

We study the rescaled probability distribution of the critical depinning force of an elastic system in a random medium. We put in evidence the underlying connection between the critical properties of the depinning transition and the extreme…

Disordered Systems and Neural Networks · Physics 2007-05-23 C. J. Bolech , Alberto Rosso

The characteristic function of the folded normal distribution and its moment function are derived. The entropy of the folded normal distribution and the Kullback--Leibler from the normal and half normal distributions are approximated using…

Methodology · Statistics 2014-02-17 Michail Tsagris , Christina Beneki , Hossein Hassani

In this article we show the existence of limiting spectral distribution of a symmetric random matrix whose entries come from a stationary Gaussian process with covariances satisfying a summability condition. We provide an explicit…

Probability · Mathematics 2013-05-15 Arijit Chakrabarty , Rajat Subhra Hazra , Deepayan Sarkar

This paper introduces an extension to the normal distribution through the polar method to capture bimodality and asymmetry, which are often observed characteristics of empirical data. The later two features are entirely controlled by a…

Statistics Theory · Mathematics 2020-08-31 Masoud Faridi , Majid Jafari Khaledi

A simple numerical method for loading of a relativistic Maxwellian-type distribution is proposed based on inverse transform sampling. The relativistic Maxwellian energy distribution is introduced as an alternative to the Maxwell-J\"{u}ttner…

Plasma Physics · Physics 2026-03-05 Takayuki Umeda

Bivariate normal distributions are often used to describe the joint probability density of a pair of random variables. These distributions arise across many domains, from telecommunications, to meteorology, ballistics, and computational…

Methodology · Statistics 2022-03-08 Emily A. Cooper , Hany Farid

In the paper, multivariate probability distributions are considered that are representable as scale mixtures of multivariate elliptically contoured stable distributions. It is demonstrated that these distributions form a special subclass of…

Probability · Mathematics 2019-12-05 Victor Korolev , Alexander Zeifman

The generalized binomial distribution in Tsallis statistics (power-law system) is explicitly formulated from the precise $q$-Stirling's formula. The $\alpha $-divergence (or $q$-divergence) is uniquely derived from the generalized binomial…

Mathematical Physics · Physics 2014-05-13 Hiroki Suyari , Antonio Maria Scarfone

The statistical properties of the multivariate Gamma-Gamma ($\Gamma \Gamma$) distribution with arbitrary correlation have remained unknown. In this paper, we provide analytical expressions for the joint probability density function (PDF),…

Information Theory · Computer Science 2016-11-18 Jiayi Zhang , Michail Matthaiou , George K. Karagiannidis , Linglong Dai

The central limit theorem provides the theoretical foundation for the universality of the normal distribution: under broad conditions, the asymptotic distribution of a sum of independent random variables approaches a Gaussian. Yet, physical…

Data Analysis, Statistics and Probability · Physics 2026-03-26 Mario Castro , José A. Cuesta