Kronecker product permutation matrices and their application to moment matrices of the normal distribution

DOI10.1016/S0047-259X(03)00047-2zbMath1030.62043OpenAlexW1969669876MaRDI QIDQ1414610

James R. Schott

Publication date: 4 December 2003

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0047-259x(03)00047-2

zbMATH Keywords

Commutation matrixGeneralized Wald statisticMoments of quadratic forms

Mathematics Subject Classification ID

Characterization and structure theory for multivariate probability distributions; copulas (62H05) Vector and tensor algebra, theory of invariants (15A72) Characterization and structure theory of statistical distributions (62E10) Basic linear algebra (15A99)

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Cites Work

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• The commutation matrix: Some properties and applications
• An antipodally symmetric distribution on the sphere
• Testing for elliptical symmetry in covariance matrix based analyses.
• The moments of products of quadratic forms in normal variables
• Higher order moments of multivariate normal distribution using matrix derivatives