DocumentCode
3066538
Title
The mutual information as a measure of statistical dependence
Author
Darbellay, Georges A.
Author_Institution
Inst. of Inf. Theory & Autom., Praha, Poland
fYear
1997
fDate
29 Jun-4 Jul 1997
Firstpage
405
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
information theory; Dobrushin´s information theorem; linear correlation; nonlinear dependence; nonparametric estimator; normalised mutual information; statistical dependence; Automation; Gaussian distribution; Hypercubes; Information theory; Mutual information; Partitioning algorithms; Probability distribution; Random variables; Stochastic processes; Vectors;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Theory. 1997. Proceedings., 1997 IEEE International Symposium on
Conference_Location
Ulm
Print_ISBN
0-7803-3956-8
Type
conf
DOI
10.1109/ISIT.1997.613342
Filename
613342
Link To Document