Random Orthogonal Transformations and their use in Some Classical Distribution Problems in Multivariate Analysis

Abstract

Orthogonal matrices having elements depending on certain random vectors provide a useful tool in various distribution problems in multivariate analysis. The method is applied to the derivation of the distributions of Hotelling's $T^2$ and Wilks' generalized variance, the Bartlett decomposition, and the Wishart distribution.