Block Versions of R functions in 'generalCorr' for Generalized Correlations and Causal Paths

Abstract

Karl Pearson developed the correlation coefficient r(X,Y) in 1890s vastly underestimates dependence between two series. Vinod(2014} develops new generalized correlation coefficients so that when r*(Y|X) > r*(X|Y) then X is the "kernel cause'' of Y. Vinod (2015) reports simulations favoring kernel causality. An R software package called 'generalCorr' (at r-project.org) computes generalized correlations, partial correlations, and plausible causal paths. This short paper describes the block versions of various R functions newly added to the 'generalCorr' package in October 2019. Newly published Vinod (2019) has the latest rendering of the theory behind causal paths including theorems with proofs. The function 'causeSummBlk(.)' is recommended for practitioners.

Keywords: generalized measure of correlation, non-parametric regression, partial correlation, observational data, endogeneity

JEL Classification: C14, C20