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

David E. Allen*, Michael McAleer

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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.

Original languageEnglish
JournalJournal of the American Statistical Association
DOIs
Publication statusAccepted/In press - 24 Jun 2020

Bibliographical note

Funding:
Michael McAleer wishes to acknowledge the financial support of the Australian Research Council and the Ministry of Science and Technology (MOST), Taiwan.
Publisher Copyright:
© 2020, © 2020 American Statistical Association.

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