Dimensionless Measures of Variability and Dependence for Multivariate Continuous Distributions

DOI10.1080/03610920601126449zbMath1315.62055OpenAlexW1975923246WikidataQ108929442 ScholiaQ108929442MaRDI QIDQ5421539

Daniel Peña, Angelika van der Linde

Publication date: 24 October 2007

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610920601126449

zbMATH Keywords

entropymutual informationindependent components

Mathematics Subject Classification ID

Multivariate distribution of statistics (62H10) Measures of association (correlation, canonical correlation, etc.) (62H20) Characterization and structure theory for multivariate probability distributions; copulas (62H05) Statistical aspects of information-theoretic topics (62B10)

Related Items (6)

Intrinsic credible regions: an objective Bayesian approach to interval estimation (with comments and rejoinder) ⋮ Test for equality of standardized generalized variance with different dimensions under high-dimensional settings ⋮ Testing equality of standardized generalized variances of \(k\) multivariate normal populations with arbitrary dimensions ⋮ Entropy measure for the quantification of upper quantile interdependence in multivariate distributions ⋮ On some entropy and divergence type measures of variability and dependence for mixed continuous and discrete variables ⋮ Dependence measures for model selection in singular spectrum analysis

Cites Work

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• Descriptive measures of multivariate scatter and linear dependence
• Relative Entropy Measures of Multivariate Dependence
• Measures of dependence for the multivariate t distribution with applications to the stock market
• Entropy expressions for multivariate continuous distributions
• Estimation of the information by an adaptive partitioning of the observation space
• Predictability: An Information-Theoretic Perspective

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