On the exact and approximate distributions of the product of a Wishart matrix with a normal vector

DOI10.1016/j.jmva.2013.07.007zbMath1280.62062OpenAlexW2096846854MaRDI QIDQ391862

Stepan Mazur, Yarema Okhrin, Taras Bodnar

Publication date: 13 January 2014

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

Full work available at URL: https://doi.org/10.1016/j.jmva.2013.07.007

zbMATH Keywords

stochastic representationWishart distributionmultivariate normal distributionintegral approximation

Mathematics Subject Classification ID

Multivariate distribution of statistics (62H10) Characterization and structure theory for multivariate probability distributions; copulas (62H05) Monte Carlo methods (65C05) Probability distributions: general theory (60E05)

Related Items (9)

Distribution of the product of a Wishart matrix and a normal vector ⋮ On the asymptotic and approximate distributions of the product of an inverse Wishart matrix and a Gaussian vector ⋮ Singular inverse Wishart distribution and its application to portfolio theory ⋮ Statistical inference for the tangency portfolio in high dimension ⋮ Distribution of the product of a singular Wishart matrix and a normal vector ⋮ Approximating the probability density function of a transformation of random variables ⋮ On the product of a singular Wishart matrix and a singular Gaussian vector in high dimension ⋮ Higher order moments of the estimated tangency portfolio weights ⋮ On the mean and variance of the estimated tangency portfolio weights for small samples

Cites Work

• Parameter priors for directed acyclic graphical models and the characterization of several probability distributions
• Moments of minors of Wishart matrices
• Properties of the singular, inverse and generalized inverse partitioned Wishart distributions
• Distribution of sum of squares and products matrices for the generalized multilinear matrix-\(T\) model
• The Matsumoto\,-\,Yor property and the structure of the Wishart distribution
• On the Product of Inverse Wishart and Normal Distributions with Applications to Discriminant Analysis and Portfolio Theory
• Predictive Distribution of Regression Vector and Residual Sum of Squares for Normal Multiple Regression Model
• Matricvariate Generalizations of the Multivariate $t$ Distribution and the Inverted Multivariate $t$ Distribution
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