A new multivariate and non-parametric association measure based on paired orthants

TL;DR

This paper introduces a novel non-parametric multivariate association measure based on paired orthants, capable of analyzing relationships among multiple variables and identifying their specific tendencies.

Contribution

It proposes a new multivariate correlation measure using paired orthants, extending non-parametric analysis to more than two variables.

Findings

Effective in analyzing relationships among 2 to 6 variables

Identifies specific tendencies of variables

Provides a new tool for multivariate correlation analysis

Abstract

Multivariate correlation analysis plays a key role in various fields such as statistics and big data analytics. In this paper, it is presented a new non-parametric association measure between more than two variables based on the concept of paired orthants. In order to evaluate the proposed methodology, different N-tuple sets (from two to six variables) have been evaluated. The presented rank correlation analysis not only evaluates the inter-relatedness of multiple variables, but also determine the specific tendency of these variables.