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Related papers: The Variance-Gamma Distribution: A Review

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We present some product representations for random variables with the Linnik, Mittag-Leffler and Weibull distributions and establish the relationship between the mixing distributions in these representations. The main result is the…

Probability · Mathematics 2016-06-28 Victor Korolev , Alexander Zeifman

The essentials of fractional calculus according to different approaches that can be useful for our applications in the theory of probability and stochastic processes are established. In addition to this, from this fractional integral one…

Mathematical Physics · Physics 2013-07-31 Nicy Sebastian

Sampling a probability distribution with an unknown normalization constant is a fundamental problem in computational science and engineering. This task may be cast as an optimization problem over all probability measures, and an initial…

Machine Learning · Statistics 2024-09-12 Yifan Chen , Daniel Zhengyu Huang , Jiaoyang Huang , Sebastian Reich , Andrew M. Stuart

It has long been agreed by academics that the inversion method is the method of choice for generating random variates, given the availability of the quantile function. However for several probability distributions arising in practice a…

Computational Finance · Quantitative Finance 2012-04-03 Asad Munir , William Shaw

We study a new family of random variables, that each arise as the distribution of the maximum or minimum of a random number $N$ of i.i.d.~random variables $X_1,X_2,\ldots,X_N$, each distributed as a variable $X$ with support on $[0,1]$. The…

Statistics Theory · Mathematics 2014-03-07 Jie Hao , Anant Godbole

The paper examines the Fractional Fourier Transform (FRFT) based technique as a tool for obtaining probability density function and its derivatives, and mainly for fitting stochastic model with the fundamental probabilistic relationships of…

Methodology · Statistics 2021-07-13 A. H. Nzokem

The Generalized Linear Model (GLM) for the Gamma distribution (glmGamma) is widely used in modeling continuous, non-negative and positive-skewed data, such as insurance claims and survival data. However, model selection for GLM depends on…

Methodology · Statistics 2018-04-24 Xin Chen , Aleksandr Y. Aravkin , R. Douglas Martin

In a recent paper, Gaunt 2020 extended Stein's method to limit distributions that can be represented as a function $g:\mathbb{R}^d\rightarrow\mathbb{R}$ of a centered multivariate normal random vector $\Sigma^{1/2}\mathbf{Z}$ with…

Probability · Mathematics 2022-09-21 Robert E. Gaunt , Heather Sutcliffe

In this paper, we discuss computational aspects to obtain accurate inferences for the parameters of the generalized gamma (GG) distribution. Usually, the solution of the maximum likelihood estimators (MLE) for the GG distribution have no…

Computation · Statistics 2017-07-26 Jorge Alberto Achcar , Pedro Luiz Ramos , Edson Zangiacomi Martinez

A new family of multivariate distributions, which shall be termed multivector variate distributions, based in the family of the multivariate contoured elliptically distribution is proposed. Several particular cases of multivector variate…

Statistics Theory · Mathematics 2018-06-26 Jose. A. Diaz-Garcia , Francisco J. Caro-Lopera , Fredy O. Perez Ramirez

A novel approach to adding two additional parameters to a family of distributions for better adaptability has been put forth. This approach yields a versatile class of distributions supported on the positive real line. We proceed to analyze…

Methodology · Statistics 2025-08-19 Subhankar Dutta , Roberto Vila , Terezinha K. A. Ribeiro

Although several nonparametric tests are available for testing population identical distributions or equal means in multiple groups problem, the Van der Waerden test has asymptotically the same efficiency as the classical one-way analysis…

Methodology · Statistics 2022-03-07 Elsayed Elamir

This paper presents a new class of probability distributions generated from the gamma distribution. For the new class proposed, we present several statistical properties, such as the risk function, the density expansions, Moment-generating…

Statistics Theory · Mathematics 2021-08-16 Cícero Carlos Ramos de Brito , Leandro Chaves Rêgo , Wilson Rosa de Oliveira

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

Matrix variate beta (MVB) distributions are used in different fields of hypothesis testing, multivariate correlation analysis, zero regression, canonical correlation analysis and etc. In this approach a unified methodology is proposed to…

Statistics Theory · Mathematics 2014-09-05 A. Bekker , M. Arashi

In this paper we propose a bimodal gamma distribution using a quadratic transformation based on the alpha-skew-normal model. We discuss several properties of this distribution such as mean, variance, moments, hazard rate and entropy…

Methodology · Statistics 2020-05-08 R. Vila , L. Ferreira , H. Saulo , F. Prataviera , E. M. M. Ortega

We obtain exact formulas for the cumulative distribution function of the variance-gamma distribution, as infinite series involving the modified Bessel function of the second kind and the modified Lommel function of the first kind. From…

Probability · Mathematics 2024-11-20 Robert E. Gaunt

Herein, we review the properties of the Amoroso distribution, the natural unification of the gamma and extreme value distribution families. Over 50 distinct, named distributions (and twice as many synonyms) occur as special cases or…

Statistics Theory · Mathematics 2015-07-14 Gavin E. Crooks

Traditional approaches to variational inference rely on parametric families of variational distributions, with the choice of family playing a critical role in determining the accuracy of the resulting posterior approximation. Simple…

Machine Learning · Statistics 2023-09-27 Martin Jankowiak , Du Phan

This work is concerned with finite range bounds on the variance of individual eigenvalues of Wigner random matrices, in the bulk and at the edge of the spectrum, as well as for some intermediate eigenvalues. Relying on the GUE example,…

Probability · Mathematics 2012-07-06 Sandrine Dallaporta
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