A simplified version of Cochran's theorem in mixed linear models

DOI10.1515/ROSE.2008.012zbMath1195.62080OpenAlexW2088139226MaRDI QIDQ5324863

Tonghui Wang, Arjun K. Gupta, Baokun Li

Publication date: 8 August 2009

Published in: Random Operators and Stochastic Equations (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1515/rose.2008.012

zbMATH Keywords

necessary and sufficient conditionssymmetric matricesmultivariate normal distributionsmatrix quadratic forms

Mathematics Subject Classification ID

Multivariate distribution of statistics (62H10) Linear regression; mixed models (62J05) Characterization and structure theory for multivariate probability distributions; copulas (62H05)

Cites Work

• MANOVA in the multivariate components of variance model
• Rank of a quadratic form in an elliptically contoured matrix random variable
• Multivariate versions of Cochran's theorems
• Multivariate versions of Cochran's theorems. II
• Wishart distributions associated with matrix quadratic forms
• Wishartness and independence of matrix quadratic forms for Kronecker product covariance structures
• Cochran's statistical theorem revisited
• Quadratic Forms in Disguised MatrixT-Variate

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