“Generalized Measures of Correlation for Asymmetry, Nonlinearity, and Beyond”: Some Antecedents on Causality
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.
|Keywords||Bravais formula, Causality, Generalized measure of correlation, Nonlinearity, Skewed correlation|
|Persistent URL||dx.doi.org/10.1080/01621459.2020.1768101, hdl.handle.net/1765/128677|
|Journal||American Statistical Association. Journal|
Allen, D.E, & McAleer, M.J. (2020). “Generalized Measures of Correlation for Asymmetry, Nonlinearity, and Beyond”: Some Antecedents on Causality. American Statistical Association. Journal. doi:10.1080/01621459.2020.1768101