Gaussian conditional structure of the second order and the Kagan classification of multivariate distributions

DOI10.1016/0047-259X(91)90006-NzbMath0739.62040MaRDI QIDQ1182747

Jacek Wesołowski

Publication date: 28 June 1992

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

zbMATH Keywords

reviewlinearity of regressionmultivariate normal distributionhomoscedasticityGaussian conditional structure of second orderKagan class

Mathematics Subject Classification ID

Characterization and structure theory for multivariate probability distributions; copulas (62H05) Characterization and structure theory of statistical distributions (62E10)

Related Items (5)

Multivariate normality via conditional normality ⋮ Variations on the classical multivariate normal theme ⋮ On some distributional and limit properties of factorizable distributions ⋮ Bivariate, multivariate, and matrix variate normal characterizations: A brief survey II ⋮ An extension of the Darmois-Skitovitch theorem to a class of dependent random variables

Cites Work

• Some characterizations of the bivariate normal distribution
• Conditional characterizations of multivariate distributions
• Can the first two conditional moments identify a mean square differentiable process?
• On determination of multivariate distribution by its marginals for the Kagan class
• On a stochasticprocess determined by the conditional expectation and the conditionalvariance
• A note on the bivariate normal distribution
• A Note on a Characterization of the Multivariate Normal Distribution
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