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A new asymmetric class of bivariate copulas for modeling dependence

ABSTRACT In this paper, we propose an asymmetric class of bivariate copulas. This class is obtained through limiting properties of the extended copula introduced by Bekrizadeh, et al. (2015), and includes some of known copulas. Some general formulas for well-known association measures and concepts of dependence of the proposed model are obtained. This paper highlights the usefulness of this new bivariate copula for modeling the interested variables whose marginal distribution effect on joint distribution isn't identical. We apply some subfamilies of this new class to model a dataset of medical science to show the superiority of presented model in comparison with the known copulas. These results will be investigated using simulation.