Title: Copula Based Independent Component Analysis

Abstract: We propose a parametric version of Independent Component Analysis (ICA) via Copulas-families of multivariate distributions that join univariate margins to multivariate distributions. Our procedure exploits the role for copula models in information theory and in measures of association, specifically: the use of copulae densities as parametric mutual information, and as measures of association on the rank statistics.