Bivariate Kumaraswamy models via modified symmetric FGM copulas: Properties and Applications in Insurance modeling

نویسنده

  • Indranil Ghosh
چکیده

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 by this method allows for greater flexibility in the values of Spearman’s correlation coefficient, ρ and Kendall’s τ . For illustrative purposes, one representative data set is utilized to exhibit the applicability of these proposed bivariate copula models.

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Bivariate Kumaraswamy Models via Modified FGM Copulas: Properties and Applications

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تاریخ انتشار 2017