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Information Gain and a General Measure of Correlation

John T. Kent
Biometrika
Vol. 70, No. 1 (Apr., 1983), pp. 163-173
Published by: Oxford University Press on behalf of Biometrika Trust
DOI: 10.2307/2335954
Stable URL: http://www.jstor.org/stable/2335954
Page Count: 11
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Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Information Gain and a General Measure of Correlation
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Abstract

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 coefficient 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.

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