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". . . the wealth of material on statistics concerning the multivariate normal distribution is quite exceptional. As such it is a very useful source of information for the general statistician and a must for anyone wanting to penetrate deeper into the multivariate field."
-Mededelingen van het Wiskundig Genootschap

"This book is a comprehensive and clearly written text on multivariate analysis from a theoretical point of view."
-The Statistician

Aspects of Multivariate Statistical Theory presents a classical mathematical treatment of the techniques, distributions, and inferences based on multivariate normal distribution. Noncentral distribution theory, decision theoretic estimation of the parameters of a multivariate normal distribution, and the uses of spherical and elliptical distributions in multivariate analysis are introduced. Advances in multivariate analysis are discussed, including decision theory and robustness. The book also includes tables of percentage points of many of the standard likelihood statistics used in multivariate statistical procedures. This definitive resource provides in-depth discussion of the multivariate field and serves admirably as both a textbook and reference.

From the Publisher:

A classical mathematical treatment of the techniques, distributions, and inferences based on the multivariate normal distribution. Introduces noncentral distribution theory, decision theoretic estimation of the parameters of a multivariate normal distribution, and the uses of spherical and elliptical distributions in multivariate analysis. Discusses recent advances in multivariate analysis, including decision theory and robustness. Also includes tables of percentage points of many of the standard likelihood statistics used in multivariate statistical procedures.

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