Nonparametric independence tests in metric spaces: What is known and what is not
Statistics Theory
2020-09-30 v1 Probability
Methodology
Statistics Theory
Abstract
Distance correlation is a recent extension of Pearson's correlation, that characterises general statistical independence between Euclidean-space-valued random variables, not only linear relations. This review delves into how and when distance correlation can be extended to metric spaces, combining the information that is available in the literature with some original remarks and proofs, in a way that is comprehensible for any mathematical statistician.
Keywords
Cite
@article{arxiv.2009.14150,
title = {Nonparametric independence tests in metric spaces: What is known and what is not},
author = {Fernando Castro-Prado and Wenceslao González-Manteiga},
journal= {arXiv preprint arXiv:2009.14150},
year = {2020}
}
Comments
18 pages with no figures