Tootfinder

This https://arxiv.org/abs/2306.01604 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_sta…

On the minimum information checkerboard copulas under fixed Kendall's rank correlation
Copulas have gained widespread popularity as statistical models to represent dependence structures between multiple variables in various applications. The minimum information copula, given a finite number of constraints in advance, emerges as the copula closest to the uniform copula when measured in Kullback-Leibler divergence. In prior research, the focus has predominantly been on constraints related to expectations on moments, including Spearman's $ρ$. This approach allows for obtaining the …

Testing Independence Between High-Dimensional Random Vectors Using Rank-Based Max-Sum Tests
Hongfei Wang, Binghui Liu, Long Feng
https://arxiv.org/abs/2404.02685

Testing Independence Between High-Dimensional Random Vectors Using Rank-Based Max-Sum Tests
In this paper, we address the problem of testing independence between two high-dimensional random vectors. Our approach involves a series of max-sum tests based on three well-known classes of rank-based correlations. These correlation classes encompass several popular rank measures, including Spearman's $ρ$, Kendall's $τ$, Hoeffding's D, Blum-Kiefer-Rosenblatt's R and Bergsma-Dassios-Yanagimoto's $τ^*$.The key advantages of our proposed tests are threefold: (1) they do not rely on specific a…