Aspects of Multivariate Statistical Theory (Wiley Series in Probability and Statistics)
Robb J. Muirhead | 2005-09-29 00:00:00 | Wiley-Interscience | 712 | Mathematics
The Wiley-Interscience Paperback Series consists of selected books that have been made more accessible to consumers in an effort to increase global appeal and general circulation. With these new unabridged softcover volumes, Wiley hopes to extend the lives of these works by making them available to future generations of statisticians, mathematicians, and scientists.
". . . 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.
Reviews
Robb Muirhead takes a strong theoretical approach to multivariate analysis much like Anderson. But although his emphasis is on distribution theory he does not restrct himslef to the multivariate normal distribution. The text is one of the best in terms of exposition and is now considered a classic. Being over 20 years old it is missing some of the latest developments.
Reviews
Multivariate statistics is probably one of the most applied, and at the same time, most theoretical aspect of Statistics. While there are various other books on this subject, this book gives, probably, one of the best, and most elegant account on the theory, particularly multivariate distribution theory, which is commonly encountered in applications. This book gives a definitive account of the techniques used to derive multivariate distributions, starting from R.A. Fisher, P L Hsu's work Pao-Lu Hsu: Collected Papers, to modern developments of A T James, and others. This book is a must-read for anyone who ventures into research in multivariate statistics. Thus, I'm glad to see a reprint paperback issue of the 1982 classic, and I wish someone will write an update in the future at the same theoretical depth and but maybe with more breadth.
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