A copula is a useful tool for constructing bivariate and/or multivariate distributions. In this article, we consider a new modified class of (Farlie-GumbelMorgenstern) FGM bivariate copula for constructing several different bivariate Kumaraswamy type copulas and discuss their structural properties, including dependence structures. It is established that construction of bivariate distributions b...

Let X and Y be two nonnegative and dependent random variables following a generalized Farlie–Gumbel–Morgenstern distribution. In this short note, we study the impact of a dependence structure of X and Y on the tail behavior of XY . We quantify the impact as the limit, as x → ∞, of the quotient of Pr(XY > x) and Pr(XY ∗ > x), where X and Y ∗ are independent random variables identically distribut...

In this paper, we are proposing a flexible method for constructing bivariate generalized Farlie-Gumbel-Morgenstern (G-FGM) copula family. The is mainly developed around the function $\phi(t)$ ($t\in [0,1]$), where $\phi$ generator of G-FGM copula. proposed construction has useful advantages. first which direct relationship between and Kendall's tau. second advantage possibility multi-parameter ...

In hydrologic risk analysis, the use of exceedance statistics are very important. this sense, we construct a random threshold model based on bivariate order statistics. The exact distribution is calculated under some well-known copulas such as independent and Farlie-Gumbel-Morgenstern (FGM) copulas. Furthermore, numerical results provided for expected value variance application in hydrology als...

In this paper we propose a new bivariate long-term distribution based on the Farlie-Gumbel-Morgenstern copula model. The proposed model allows for presence of censored data and covariates in cure parameter. For inferential purpose Bayesian approach via Markov Chain Monte Carlo (MCMC) is considered. Further, some discussions selection criteria are given. order to examine outlying influential obs...

Recently, Chen (2011) studied the finite-time ruin probability in a discrete-time risk model in which the insurance and financial risks form a sequence of independent and identically distributed random pairs with common bivariate Farlie–Gumbel–Morgenstern (FGM) distribution. The parameter θ of the FGMdistribution governs the strength of dependence, with a smaller value of θ corresponding to a l...