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We propose a new family of copulas generalizing the Farlie-Gumbel-Morgenstern family and generated by two univariate functions. The main feature of this family is to permit the modeling of high positive dependence. In particular, it is…

Statistics Theory · Mathematics 2011-03-31 Cécile Amblard , Stéphane Girard

In this paper, we introduce a bivariate exponentaited generalized Weibull-Gompertz distribution. The model introduced here is of Marshall-Olkin type. Several properties are studied such as bivariate probability density function and it is…

Statistics Theory · Mathematics 2015-01-19 M. A. EL-Damcese , Abdelfattah Mustafa , M. S. Eliwa

Univariate Weibull distribution is a well-known lifetime distribution and has been widely used in reliability and survival analysis. In this paper, we introduce a new family of bivariate generalized Weibull (BGW) distributions, whose…

Methodology · Statistics 2024-08-29 Ashok Kumar Pathak , Mohd. Arshad , Qazi J. Azhad , Mukti Khetan , Arvind Pandey

We propose an approach to construct a new family of generalized Farlie-Gumbel-Morgenstern (GFGM) copulas that naturally scales to high dimensions. A GFGM copula can model moderate positive and negative dependence, cover different types of…

Statistics Theory · Mathematics 2022-09-29 Christopher Blier-Wong , Hélène Cossette , Sébastien Legros , Etienne Marceau

This paper provides bifactor gamma distribution, trivariate gamma distribution and two copula families on [0, 1] n obtained from the Laplace transforms of the multivariate gamma distribution and the multi-factor gamma distribution given by…

Statistics Theory · Mathematics 2016-11-23 Philippe Bernardoff

A new generator of univariate continuous distributions, with two additional parameters, called the Log-Lindley generated family is introduced. Some special distributions in the new family are presented. Some mathematical properties of the…

Methodology · Statistics 2017-05-11 Lazhar Benkhelifa

A new class of distributions, called Generalized One Parameter Polynomial Exponential-G family of distributions is proposed for modelling lifetime data. An account of the structural and reliability properties of the new class is presented.…

Applications · Statistics 2020-06-11 Sudhansu S. Maiti , Sukanta Pramanik

In this paper, we give a method to construct "good" exponential families systematically by representation theory. More precisely, we consider a homogeneous space $G/H$ as a sample space and construct an exponential family invariant under…

Statistics Theory · Mathematics 2022-10-14 Koichi Tojo , Taro Yoshino

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 offer a new perspective on risk aggregation with FGM copulas. Along the way, we discover new results and revisit existing ones, providing simpler formulas than one can find in the existing literature. This paper builds on two novel…

Statistics Theory · Mathematics 2022-08-01 Christopher Blier-Wong , Hélène Cossette , Etienne Marceau

In this paper, we introduce a new class of bivariate distributions called the bivariate exponentiated extended Weibull distributions. The model introduced here is of Marshall-Olkin type. This new class of bivariate distributions contains…

Methodology · Statistics 2015-07-28 Rasool Roozegar , Ali Akbar Jafari

In this paper we develop a bivariate discrete generalized exponential distribution, whose marginals are discrete generalized exponential distribution as proposed by Nekoukhou, Alamatsaz and Bidram ("Discrete generalized exponential…

Methodology · Statistics 2017-01-16 Vahid Nekoukhou , Debasis Kundu

Many types of bounded data defined on the unit interval arise naturally as ratios of the form $X/(X + Y)$. In the existing literature, the main statistical models proposed for this type of bounded data typically based on the assumption that…

Methodology · Statistics 2026-03-04 Roberto Vila , Felipe Quintino , Marcelo Bourguignon

The literature has covered the features and uses of the traditional univariate and bivariate logistic distributions in great detail. It is reasonable to wonder, though, if logistic marginals and conditionals could exhibit a similar…

Applications · Statistics 2023-11-15 Banoth Veeranna

In this paper, we introduce a new bivariate distribution we called it bivariate expo- nentiated modified Weibull extension distribution (BEMWE). The model introduced here is of Marshall-Olkin type. The marginals of the new bivariate…

Statistics Theory · Mathematics 2015-01-16 A. El-Gohary , M. El-Morshedy

We introduce an extended d-variate Farlie-Gumbel-Morgenstern (FGM) copula that incorporates additional parameters based on Legendre polynomials to enhance the representation of multivariate dependence structures. Within an i.i.d. framework,…

Methodology · Statistics 2025-09-10 Mous-Abou Hamadou , Martial Longla

Recently it has been observed that the bivariate generalized linear failure rate distribution can be used quite effectively to analyze lifetime data in two dimensions. This paper introduces a more general class of bivariate distributions.…

Applications · Statistics 2015-08-06 Rasool Roozegar , Ali Akbar Jafari

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

We characterize bivariate natural exponential families having the diagonal of the variance function of the form \[ \textrm{diag} V(m_1,m_2)=\left(Am_1^2+am_1+bm_2+e,Am_2^2+cm_1+dm_2+f\right), \] with $A<0$ and $a,\ldots,f\in\mathbb{R}$. The…

Statistics Theory · Mathematics 2015-04-22 Joanna Matysiak

In this paper we develop a very general class of bivariate discrete distributions. The basic idea is very simple. The marginals are obtained by taking the random geometric sum of a baseline distribution function. The proposed class of…

Methodology · Statistics 2018-05-22 Debasis Kundu
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