Multivariate Observations

G. A. F. Seber

ISBN 10: 047188104X / ISBN 13: 9780471881049

Published by John Wiley & Sons, 1984

About this Item

Mild wear to jacket. Spine cocked.

Seller Inventory # 1136432

Bibliographic Details

• Title: Multivariate Observations
• Publisher: John Wiley & Sons
• Publication Date: 1984
• Language: English
• ISBN 10: 047188104X
• ISBN 13: 9780471881049
• Binding: hardcover
• Condition: very good
• Dust Jacket Condition: very good
• Seller catalogs:
  • Mathematics

About this title

Synopsis

WILEY-INTERSCIENCE PAPERBACK SERIES

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.

"In recent years many monographs have been published on specialized aspects of multivariate data-analysis–on cluster analysis, multidimensional scaling, correspondence analysis, developments of discriminant analysis, graphical methods, classification, and so on. This book is an attempt to review these newer methods together with the classical theory. . . . This one merits two cheers."
–J. C. Gower, Department of Statistics
Rothamsted Experimental Station, Harpenden, U.K.
Review in Biometrics, June 1987

Multivariate Observations is a comprehensive sourcebook that treats data-oriented techniques as well as classical methods. Emphasis is on principles rather than mathematical detail, and coverage ranges from the practical problems of graphically representing high-dimensional data to the theoretical problems relating to matrices of random variables. Each chapter serves as a self-contained survey of a specific topic. The book includes many numerical examples and over 1,100 references.

From the Publisher

This up-to-date, comprehensive sourcebook treats data-oriented techniques as well as classical methods. Emphasis is on principles rather than mathematical detail, and coverage ranges from the practical problems of graphically representing high dimensional data to the theoretical problems relating to matrices of random variables. Each chapter serves as a self-contained survey of a specific topic. Includes many numerical examples, and over 1,100 references.