Quantifying and testing dependence to categorical variables
Statistics Theory
2025-10-03 v2 Statistics Theory
Abstract
We suggest a dependence coefficient between a categorical variable and some general variable taking values in a metric space. We derive important theoretical properties and study the large sample behaviour of our suggested estimator. Moreover, we develop an independence test which has an asymptotic -distribution if the variables are independent and prove that this test is consistent against any violation of independence. The test is also applicable to the classical~-sample problem with possibly high- or infinite-dimensional distributions. We discuss some extensions, including a variant of the coefficient for measuring conditional dependence.
Cite
@article{arxiv.2509.10268,
title = {Quantifying and testing dependence to categorical variables},
author = {Siegfried Hörmann and Daniel Strenger-Galvis},
journal= {arXiv preprint arXiv:2509.10268},
year = {2025}
}
Comments
We added some references to the K-sample problem and included a related test in our simulations