Geometric Estimation of Multivariate Dependency

Geometric Estimation of Multivariate Dependency

This paper proposes a geometric estimator of dependency between a pair of multivariate random variables. The proposed estimator of dependency is based on a randomly permuted geometric graph (the minimal spanning tree) over the two multivariate samples. This estimator converges to a quantity that we...

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Bibliographic Details
Main Authors: Salimeh Yasaei Sekeh, Alfred O. Hero
Format: Article
Language:English
Published: MDPI AG 2019-08-01
Series:Entropy
Subjects:
Henze–Penrose mutual information
Friedman–Rafsky test statistic
geometric mutual information
convergence rates
bias and variance tradeoff
optimization
minimal spanning trees
Online Access:https://www.mdpi.com/1099-4300/21/8/787

Internet

https://www.mdpi.com/1099-4300/21/8/787

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