Abstract
Multivariate dependence measures based on relative entropy and concordance have previously been proposed by the author. The theory of the sample versions of these dependence measures and their standard errors is completed here for the case of mixed continuous and categorical variables; some new results for estimation of a functional of a multivariate density are needed. The measures are useful for exploratory data analysis to determine good sets of predictor variables for response variables. They are illustrated in analysis of two large data sets. The substantial contributions are unification of dependence measures for mixed types of variables, and the generality of the relative entropy measures for conditional and regression dependences.
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