How should one quantify the strength of association between two random variables without
bias for relationships of a specific form? Despite its conceptual simplicity, this notion of …

系统综述了自19 世纪开始至今常用的统计相关性的方法, 例如Pearson 和Spearman 相关系数,
CorGc 和CovGc 相关性及距离相关性方法. 重点介绍了2011 年提出的MIC 方法以及由此引发的 …

We demonstrate that a popular class of non-parametric mutual information (MI) estimators
based on k-nearest-neighbor graphs requires number of samples that scales exponentially …

Background To construct gene co-expression networks, it is necessary to evaluate the
correlation between different gene expression profiles. However, commonly used correlation …

Understanding and developing a correlation measure that can detect general dependencies
is not only imperative to statistics and machine learning, but also crucial to general scientific …

A measure of dependence is said to be equitable if it gives similar scores to equally noisy
relationships of different types. Equitability is important in data exploration when the goal is …

An empirical study of the maximal and total information coefficients and leading measures
of dependence Page 1 The Annals of Applied Statistics 2018, Vol. 12, No. 1, 123–155 https://doi.org/10.1214/17-AOAS1093 …

Microbes can be found almost everywhere in the world. They are not isolated, but rather
interact with each other and establish connections with their living environments. Studying …

Nonlinear dependence is general in regulation mechanism of gene regulatory networks
(GRNs). It is vital to properly measure or test nonlinear dependence from real data for …

Székely, Rizzo and Bakirov (Ann. Statist. 35 (2007) 2769–2794) and Székely and Rizzo
(Ann. Appl. Statist. 3 (2009) 1236–1265), in two seminal papers, introduced the powerful …