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An Introduction to Multivariate Statistical Analysis - Theodore W. Anderson

An Introduction to Multivariate Statistical Analysis

Buch | Hardcover
752 Seiten
2003 | 3rd edition
Wiley-Interscience (Verlag)
978-0-471-36091-9 (ISBN)
CHF 289,95 inkl. MwSt
Uses the method of maximum likelihood to a large extent to ensure reasonable, and in some cases optimal procedures. This work treats the basic and important topics in multivariate statistics.
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.

THEODORE W. ANDERSON, Professor Emeritus of Statistics and Economics at Stanford University, earned his PhD in mathematics at Princeton University. He is the author of The Statistical Analysis of Time Series, published by Wiley, as well as The New Statistical Analysis of Data and A Bibliography of Multivariate Statistical Analysis. Anderson is a member of the National Academy of Sciences and a Fellow of the Institute of Mathematical Statistics, the American Statistical Association, the Econometric Society, and the American Academy of Arts and Sciences.

Preface to the Third Edition. Preface to the Second Edition.

Preface to the First Edition.

1. Introduction.

2. The Multivariate Normal Distribution.

3. Estimation of the Mean Vector and the Covariance Matrix.

4. The Distributions and Uses of Sample Correlation Coefficients.

5. The Generalized T2-Statistic.

6. Classification of Observations.

7. The Distribution of the Sample Covariance Matrix and the Sample Generalized Variance.

8. Testing the General Linear Hypothesis: Multivariate Analysis of Variance

9. Testing Independence of Sets of Variates.

10. Testing Hypotheses of Equality of Covariance Matrices and Equality of Mean Vectors and Covariance Matrices.

11. Principal Components.

12. Cononical Correlations and Cononical Variables.

13. The Distributions of Characteristic Roots and Vectors.

14. Factor Analysis.

15. Pattern of Dependence; Graphical Models.

Appendix A: Matrix Theory.

Appendix B: Tables.

References.

Index.

Erscheint lt. Verlag 8.8.2003
Reihe/Serie Wiley Series in Probability and Statistics
Zusatzinfo Tables: 11 B&W, 0 Color; Graphs: 33 B&W, 0 Color
Sprache englisch
Maße 163 x 244 mm
Gewicht 1188 g
Themenwelt Mathematik / Informatik Mathematik Analysis
Mathematik / Informatik Mathematik Statistik
Mathematik / Informatik Mathematik Wahrscheinlichkeit / Kombinatorik
ISBN-10 0-471-36091-0 / 0471360910
ISBN-13 978-0-471-36091-9 / 9780471360919
Zustand Neuware
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