Discovering Association with Copula Entropy
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Publication:6322831
arXiv1907.12268MaRDI QIDQ6322831
Jian Ma
Publication date: 29 July 2019
Abstract: Discovering associations is of central importance in scientific practices. Currently, most researches consider only linear association measured by correlation coefficient, which has its theoretical limitations. In this paper, we propose a new method for discovering association with copula entropy -- a universal applicable association measure for not only linear cases, but nonlinear cases. The advantage of the method based on copula entropy over traditional method is demonstrated on the NHANES data by discovering more biomedical meaningful associations.
Has companion code repository: https://github.com/majianthu/nhanes
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