An Introduction to Multivariate Statistical Analysis (Wiley Series in Probability and Statistics)

✍ Scribed by T. W. Anderson

• Publisher: Wiley-Interscience
• Year: 2003
• Tongue: English
• Leaves: 739
• Edition: 3
• Category: Library

✦ Synopsis

Perfected over three editions and more than forty years, this field- and classroom-tested reference: Uses the method of maximum likelihood to a large extent to ensure reasonable, and in some cases optimal procedures. Treats all the basic and important topics in multivariate statistics. Adds two new chapters, along with a number of new sections. Provides the most methodical, up-to-date information on MV statistics available.

✦ Table of Contents

Title Page......Page 1
CONTENTS......Page 5
Preface to the Third Edition......Page 13
Preface to the Second Edition......Page 15
Preface to the First Edition......Page 17
1. Introduction......Page 19
2. The Multivariate Normal Distribution......Page 24
3. Estimation of the Mean Vector and the Covariance Matrix......Page 84
4. The Distributions and Uses of Sample Correlation Coefficients......Page 133
5. The Generalized T2-Statistic......Page 188
6. Classification of Observations......Page 225
7. The Distribution of the Sample Covariance Matrix and the Sample Generalized Variance......Page 269
8. Testing the General Linear Hypothesis; Multivariate Analysis of Variance......Page 309
9. Testing Independence of Sets of Variates......Page 399
10. Testing Hypotheses of Equality of Covariance Matrices and Equality of Mean Vectors and Covariance Matrices......Page 429
11. Principal Components......Page 477
12. Canonical Correlations and Canonical Variables......Page 505
13. The Distributions of Characteristic Roots and Vectors......Page 546
14. Factor Analysis......Page 587
15. Patterns of Dependence; Graphical Models......Page 613
A. Matrix Theory......Page 642
B. Tables......Page 669
References......Page 705
INDEX......Page 731