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A comprehensive and self-contained introduction to the field, carefully balancing mathematical theory and practical applications. It starts at an elementary level, developing concepts of multivariate distributions from first principles. After a chapter on the multivariate normal distribution reviewing the classical parametric theory, methods of estimation are explored using the plug-in principles as well as maximum likelihood. Two chapters on discrimination and classification, including logistic regression, form the core of the book, followed by methods of testing hypotheses developed from heuristic principles, likelihood ratio tests and permutation tests. Finally, the powerful self-consistency principle is used to introduce principal components as a method of approximation, rounded off by a chapter on finite mixture analysis.
- Sales Rank: #10378868 in Books
- Published on: 2010-11-24
- Original language: English
- Number of items: 1
- Dimensions: 9.68" h x 1.65" w x 7.44" l, 2.22 pounds
- Binding: Paperback
- 715 pages
Review
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From a review:
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION
"... is actually a very unique book that differs considerably from other multivariate texts. Flury should be applauded for his intention and effort to produce a new type of multivariate book that is neither a comprehensive theoretical treatise nor an encyclopedic methods cookbook. ... it is a welcome addition to the multivariate statistics literature. This is a well-written book with vivid and lively discussions."
Most helpful customer reviews
34 of 34 people found the following review helpful.
excellent introductory book on multivariate analysis
By Michael R. Chernick
This is a nice well balanced text on multivariate analysis very suitable as a first course for graduate students. It provides a very good treatment of principal component analysis and discriminant analysis. Some specialized topics such as structural equations and factor analysis are not covered.
13 of 17 people found the following review helpful.
Terrible introductory book for graduate students in stats
By lpac
Lack of clear examples made this book a terrible supplement to my multivariate statistics curriculum. I would recommend 'Applied Multivariate Statistical Analysis' by Johnson and Wichern for the graduate student first tackling this difficult topic.
4 of 5 people found the following review helpful.
Excellent
By rc
This is a wonderful book. Flury goes out of his way to provide thoughtful explanations rather than just the mathematical machinery. Thankfully this is not another bland exhaustive book of multivariate methods/recipes, but has carefully chosen topics including discriminant analysis, logistic regression, mixture models and the EM algorithm.
It was fun working through this book.
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