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

Robert A. Wijsman
The Annals of Mathematical Statistics
Vol. 28, No. 2 (Jun., 1957), pp. 415-423
Stable URL: http://www.jstor.org/stable/2237163
Page Count: 9
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Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Random Orthogonal Transformations and their use in Some Classical Distribution Problems in Multivariate Analysis
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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.

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