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Dependence Meaure for non-additive model

Abstract

We proposed a new statistical dependency measure called Copula Dependency Coefficient(CDC) for two sets of variables based on marginal distribution function estimation. It is robust to outliers, easy to implement, powerful and appropriate to high-dimensional variables. These properties are important in many applications. Experimental results show that CDC can detect the dependence between variables in both additive and non-additive models.

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