Characterization of matrix variate normal distributions

DOI10.1016/0047-259X(92)90058-NzbMath0745.62052OpenAlexW2006849814MaRDI QIDQ1186774

T. Varga, Arjun K. Gupta

Publication date: 28 June 1992

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

Full work available at URL: https://doi.org/10.1016/0047-259x(92)90058-n

zbMATH Keywords

random matricesconditional distributionsregressionlinear independencejoint matrix variate normal distribution

Mathematics Subject Classification ID

Characterization and structure theory for multivariate probability distributions; copulas (62H05)

Related Items (6)

Exact SOR convergence regions for a general class of \(p\)-cyclic matrices ⋮ Sparse Hanson-Wright inequalities for subgaussian quadratic forms ⋮ Concentration of measure bounds for matrix-variate data with missing values ⋮ Bivariate, multivariate, and matrix variate normal characterizations: A brief survey II ⋮ Characterizations of some continuous distributions ⋮ Gemini: graph estimation with matrix variate normal instances

Cites Work

• Characterizations of multivariate normality II. Through linear regressions
• Characterizations of multivariate normality: I. Through independence of some statistics
• A note on the bivariate normal distribution

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