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Biometrika 1983 70(1):163-173; doi:10.1093/biomet/70.1.163
© 1983 by Biometrika Trust
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Information gain and a general measure of correlation

JOHN T. KENT

Department of Statistics, University of Leeds

Given a parametric model of dependence between two random quantities, X and Y, the notion of information gain can be used to define a measure of correlation. This definition of correlation generalizes both the usual product-moment correlation coeffi cient for the bivariate normal model and the multiple correlation coefficient in the standard linear regression model. The use of this information-based correlation in a descriptive statistical analysis is examined and several examples are given.

Key Words: Conditional correlation • Joint correlation • Kullback Leibler information gain • Likelihood ratio test • Akaike's information criterion • Robustness


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