Functions of singular random matrices with applications

DOI10.1007/BF02595414zbMath1087.62061OpenAlexW1968157170MaRDI QIDQ820211

José A. Díaz-García, Ramón Gutiérrez-Jáimez

Publication date: 6 April 2006

Published in: Test (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/bf02595414

zbMATH Keywords

Hausdorff measureinverse singular distributionsinverse Wishart and pseudo-Wishart singular distributionsmatrix-variate inverse beta and \(F\) distributions

Mathematics Subject Classification ID

Multivariate distribution of statistics (62H10) Multivariate analysis (62H99) Bayesian inference (62F15) Characterization and structure theory for multivariate probability distributions; copulas (62H05) Theory of matrix inversion and generalized inverses (15A09) Random matrices (algebraic aspects) (15B52)

Related Items (4)

A note about measures, Jacobians and Moore-Penrose inverse ⋮ Matrix variate Birnbaum-Saunders distribution under elliptical models ⋮ Singular matrix variate Birnbaum-Saunders distribution under elliptical models ⋮ Pseudo-inverse multivariate/matrix-variate distributions

Cites Work

• Bessel functions of matrix argument
• On singular Wishart and singular multivariate beta distributions
• Wishart and pseudo-Wishart distributions and some applications to shape theory
• Proof of the conjectures of H. Uhlig on the singular multivariate beta and the Jacobian of a certain matrix transformation
• Singular random matrix decompositions: Jacobians
• The 70th anniversary of the distribution of random matrices: A survey
• The density of the Moore-Penrose inverse of a random matrix
• Multivariate calculation. Use of the continuous groups
• Wishart and pseudo-Wishart distributions under elliptical laws and related distributions in the shape theory context
• Distribution of the generalised inverse of a random matrix and its applications
• Multivariate Beta Distributions and Independence Properties of the Wishart Distribution
• Linear Statistical Inference and its Applications
• Normal Multivariate Analysis and the Orthogonal Group
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