The Farlie-Gumbel-Morgenstern (FGM) family has been investigated in detail for various continuous marginals such as Cauchy, normal, exponential, gamma, Weibull, lognormal and others. It has been a popular model for the bivariate distribution with mild dependence. However, bivariate FGMs with continuous marginals on a bounded support discussed in the literature are only those with uniform or power marginals. In this paper we study the bivariate FGM family with marginals given by the recently proposed two-sided power (TSP) distribution. Since this family of bounded continuous distributions is very flexible, the properties of the FGM family with TSP marginals could serve as an indication of the structure of the FGM distribution with arbitrary ...
AbstractWe introduce two new bivariate gamma distributions based on a characterizing property involv...
In this article, we study several properties such as marginal and condi-tional distributions, joint ...
Abstract. The set of dependent random variables with multivariate Farlie-Gumbel-Morgenstern (FGM) di...
summary:In this paper, we study a general structure for the so-called Farlie-Gumbel-Morgenstern (FGM...
summary:In this paper, we study a general structure for the so-called Farlie-Gumbel-Morgenstern (FGM...
summary:In this paper, we study a general structure for the so-called Farlie-Gumbel-Morgenstern (FGM...
AbstractHuang and Kotz (1999) [17] considered a modification of the Farlie–Gumbel–Morgenstern (FGM) ...
AbstractParametric families of continuous bivariate distributions with given margins that include in...
AbstractParametric families of continuous bivariate distributions with given margins that include in...
Probability distributions and their families play an effective role in statistical modeling and stat...
International audienceWe propose a new family of copulas generalizing the Farlie-Gumbel-Morgenstern ...
We are concerned with the flexible parametric analysis of bivariate survival data. Elsewhere, we arg...
In this paper, the earlier work on so-called \u22power-normal distribution\u22 is extended to a mult...
We construct a bivariate distribution of (X, Y ) by assuming that the conditional distribution of Y ...
We construct a bivariate distribution of (X, Y ) by assuming that the conditional distribution of Y ...
AbstractWe introduce two new bivariate gamma distributions based on a characterizing property involv...
In this article, we study several properties such as marginal and condi-tional distributions, joint ...
Abstract. The set of dependent random variables with multivariate Farlie-Gumbel-Morgenstern (FGM) di...
summary:In this paper, we study a general structure for the so-called Farlie-Gumbel-Morgenstern (FGM...
summary:In this paper, we study a general structure for the so-called Farlie-Gumbel-Morgenstern (FGM...
summary:In this paper, we study a general structure for the so-called Farlie-Gumbel-Morgenstern (FGM...
AbstractHuang and Kotz (1999) [17] considered a modification of the Farlie–Gumbel–Morgenstern (FGM) ...
AbstractParametric families of continuous bivariate distributions with given margins that include in...
AbstractParametric families of continuous bivariate distributions with given margins that include in...
Probability distributions and their families play an effective role in statistical modeling and stat...
International audienceWe propose a new family of copulas generalizing the Farlie-Gumbel-Morgenstern ...
We are concerned with the flexible parametric analysis of bivariate survival data. Elsewhere, we arg...
In this paper, the earlier work on so-called \u22power-normal distribution\u22 is extended to a mult...
We construct a bivariate distribution of (X, Y ) by assuming that the conditional distribution of Y ...
We construct a bivariate distribution of (X, Y ) by assuming that the conditional distribution of Y ...
AbstractWe introduce two new bivariate gamma distributions based on a characterizing property involv...
In this article, we study several properties such as marginal and condi-tional distributions, joint ...
Abstract. The set of dependent random variables with multivariate Farlie-Gumbel-Morgenstern (FGM) di...