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• W2896726088 abstract "In this paper, the defining properties of a valid measure of the dependence between two random variables are reviewed and complemented with two original ones, shown to be more fundamental than other usual postulates. While other popular choices are proved to violate some of these requirements, a class of dependence measures satisfying all of them is identified. One particular measure, that we call the Hellinger correlation, appears as a natural choice within that class due to both its theoretical and intuitive appeal. A simple and efficient nonparametric estimator for that quantity is proposed. Synthetic and real-data examples finally illustrate the descriptive ability of the measure, which can also be used as test statistic for exact independence testing." @default.
• W2896726088 created "2018-10-26" @default.
• W2896726088 creator A5021848861 @default.
• W2896726088 creator A5037753859 @default.
• W2896726088 date "2018-10-24" @default.
• W2896726088 modified "2023-10-16" @default.
• W2896726088 title "The Hellinger Correlation" @default.
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• W2896726088 hasPublicationYear "2018" @default.
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