Discovering Association with Copula Entropy
This addresses the limitation of linear correlation in scientific discovery, though it appears incremental as it extends existing association measures.
The authors tackled the problem of discovering associations beyond linear correlation by proposing a method based on copula entropy, which they demonstrated on NHANES data to find more biomedical associations.
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.