“Generalized Measures of Correlation for Asymmetry, Nonlinearity, and Beyond”: Some Antecedents on Causality

B-Tier
Journal: Journal of the American Statistical Association
Year: 2022
Volume: 117
Issue: 537
Pages: 214-224

Score contribution per author:

1.005 = (α=2.01 / 2 authors) × 1.0x B-tier

α: calibrated so average coauthorship-adjusted count equals average raw count

Abstract

This note comments on the generalized measure of correlation (GMC) that was suggested by Zheng, Shi, and Zhang. The GMC concept was partly anticipated in some publications over 100 years earlier by Yule in the Proceedings of the Royal Society, and by Kendall. Other antecedents discussed include work on dependency by Renyi and Doksum and Samarov, together with the Yule–Simpson paradox. The GMC metric partly extends the concept of Granger causality, so that we consider causality, graphical analysis and alternative measures of dependency provided by copulas.

Technical Details

RePEc Handle
repec:taf:jnlasa:v:117:y:2022:i:537:p:214-224
Journal Field
Econometrics
Author Count
2
Added to Database
2026-01-24