Optimal Transport Dependency
Axel Munk (Georg August University of Göttingen)
E18-304
Abstract: Finding meaningful ways to determine the dependency between two random variables and is a timeless statistical endeavor with vast practical relevance. In recent years, several concepts that aim to extend classical means (such as the Pearson correlation or rank-based coefficients like Spearman’s ) to more general spaces have been introduced and popularized, a well-known example being the distance correlation. In this talk, we propose and study an alternative framework for measuring statistical dependency, the transport dependency ≥ 0 (TD),…
