Some alternative bivariate Kumaraswamy-type distributions via copula with application in risk management

Bivariate Kumaraswamy Models via Modified Symmetric FGM Copulas: Properties and Applications in Insurance Modeling

“…For details on this see Ghosh et al (2016) For the sake of notational simplicity and for the remainder of the article, we call (3.4)…”

“…Here, we consider one application for the four proposed bivariate Kumaraswamy copula models to a heavily used data set, originally considered by (1981,1986) as well as in Ghosh et al (2016). This data set contains two variables:…”

“…of bivariate Kumaraswamy models. Again, in Ghosh et al (2016), the authors discussed some copula based approach to construct several bivariate Kumaraswamy type models along with an application to a real life data set focusing on financial risk assessment.…”

“…This article is a follow up paper of Ghosh et al (2016), in which, we examine in details the utility of well known bivariate FGM copula by a slight modification to allow greater flexibility in modeling various types of data sets (in the sense of those results described in details in Rodriguez-Lallena et al (2004)). In this article we start with a standard Kumaraswamy quantile function from two independent Kumaraswamy distributions (with two different sets of shape parameters) and construct the corresponding bivariate copula with different shape parameters.…”

Bivariate Kumaraswamy Models via Modified FGM Copulas: Properties and Applications

“…Arnold and Ghosh (2017) discussed some different strategies for constructing legitimate bivariate KW models via Arnold-Ng type copula approach. Recently, Ghosh and Ray (2016) discussed some copula based approach to construct several bivariate KW type models along with an application to a real life data set focusing on financial risk assessment. This article is a follow up paper to Ghosh and Ray (2016), in which we examine in detail the utility of a well-known bivariate FGM copula by a slight modification to allow greater flexibility in modeling various types of data sets.…”