The mutual information as a measure of statistical dependence

22 November 2002

conference paper
Published by Institute of Electrical and Electronics Engineers (IEEE)

p. 405
https://doi.org/10.1109/isit.1997.613342

Abstract

The mutual information I, if appropriately normalised, can serve as a measure of correlation. In encompassing nonlinear dependences, it generalises the classical measures of linear correlation. An efficient nonparametric estimator of I can be derived from Dobrushin's (1963) information theorem.

Keywords

MUTUAL INFORMATION
PROBABILITY DISTRIBUTION
RANDOM VARIABLES
VECTORS
INFORMATION THEORY
AUTOMATION
STOCHASTIC PROCESSES
PARTITIONING ALGORITHMS
GAUSSIAN DISTRIBUTION
HYPERCUBES

This publication has 1 reference indexed in Scilit:

On measures of dependence
Acta Mathematica Hungarica, 1959

Cited by 3 articles