An Estimator of Mutual Information and its Application to Independence Testing

An Estimator of Mutual Information and its Application to Independence Testing

This paper proposes a novel estimator of mutual information for discrete and continuous variables. The main feature of this estimator is that it is zero for a large sample size n if and only if the two variables are independent. The estimator can be used to construct several histograms, compute esti...

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Bibliographic Details
Main Author: Joe Suzuki
Format: Article
Language:English
Published: MDPI AG 2016-03-01
Series:Entropy
Subjects:
mutual information
kernel
independence testing
Hilbert-Schmidt independence criterion (HSIC)
minimum description length (MDL) principle
histogram
Online Access:http://www.mdpi.com/1099-4300/18/4/109

Internet

http://www.mdpi.com/1099-4300/18/4/109

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