Mutual information as a measure of multivariate association: analytical properties and statistical estimation

DOI10.1080/00949655.2011.575782zbMath1431.62248OpenAlexW2013987542MaRDI QIDQ5300813

Friedrich Schmid, Thomas Blumentritt

Publication date: 28 June 2013

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2011.575782

zbMATH Keywords

histogrammutual informationMonte Carlo simulationKullback-Leibler divergencenonparametric estimationnearest neighbour estimatorBernstein estimatorcopula densitybeta kernel

Mathematics Subject Classification ID

Density estimation (62G07) Asymptotic properties of nonparametric inference (62G20) Measures of association (correlation, canonical correlation, etc.) (62H20) Characterization and structure theory for multivariate probability distributions; copulas (62H05)

Related Items (8)

Non-parametric estimation of mutual information through the entropy of the linkage ⋮ New copulas based on general partitions-of-unity and their applications to risk management ⋮ Non-parametric estimation of copula based mutual information ⋮ Comparison, utility, and partition of dependence under absolutely continuous and singular distributions ⋮ On reconsidering entropies and divergences and their cumulative counterparts: Csiszár's, DPD's and Fisher's type cumulative and survival measures ⋮ A note on the notion of informative composite density ⋮ Information measures of kernel estimation ⋮ Testing independence based on Bernstein empirical copula and copula density

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