Dr Gery Geenens
Fri, 09/11/2018 - 4:00pm
RC-4082, The Red Centre, UNSW
In this work, 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.
The paper can be found at https://arxiv.org/abs/1810.10276