ResearchTrend.AI
  • Papers
  • Communities
  • Events
  • Blog
  • Pricing
Papers
Communities
Social Events
Terms and Conditions
Pricing
Parameter LabParameter LabTwitterGitHubLinkedInBlueskyYoutube

© 2025 ResearchTrend.AI, All rights reserved.

  1. Home
  2. Papers
  3. 2008.11619
109
52
v1v2v3v4 (latest)

On the power of Chatterjee rank correlation

26 August 2020
Hongjian Shi
Mathias Drton
Fang Han
ArXiv (abs)PDFHTML
Abstract

Recently, Chatterjee (2020) introduced a new rank correlation that attracts many statisticians' attention. This paper compares it to three already well-used rank correlations in literature, Hoeffding's DDD, Blum-Kiefer-Rosenblatt's RRR, and Bergsma-Dassios-Yanagimoto's τ∗\tau^*τ∗. Three criteria are considered: (i) computational efficiency, (ii) consistency against fixed alternatives, and (iii) power against local alternatives. Our main results show the unfortunate rate sub-optimality of Chatterjee's rank correlation against three popular local alternatives in independence testing literature. Along with some recent computational breakthroughs, they favor the other three in many settings.

View on arXiv
Comments on this paper