T. W. Anderson

An Introduction to Multivariate Statistical Analysis

• Gebundenes Buch

Produktbeschreibung

The Second Edition of An Introduction to Multivariate Statistical Analysis has become a standard in the field. Since its publication, several advances have been made in multivariate (MV) statistical analysis. Maintaining the previous edition's mathematically rigorous development of statistical models, the Third Edition substantially revises and adds to the original text to bring statisticians up to date with recent developments in the field.

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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.

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Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.

Produktdetails

• Wiley Series in Probability and Statistics
• Verlag: Wiley & Sons
• 3. Aufl.
• Seitenzahl: 752
• Erscheinungstermin: 8. August 2003
• Englisch
• Abmessung: 240mm x 161mm x 44mm
• Gewicht: 1165g
• ISBN-13: 9780471360919
• ISBN-10: 0471360910
• Artikelnr.: 11452462

Autorenporträt

Anderson wrote this book as a simple visual tool to make clear that while appearing normal, living with Chronic Fatigue is a life-changing and controlling disease with a complex combination and fluctuation of symptoms that cannot be seen. Adjusting to change, letting go of control, focusing on wellbeing, practicing yoga, and simply trusting and accepting what is has been a profound learning experience for Anderson.

Inhaltsangabe

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.

Rezensionen

"...suitable for a graduate-level course on multivariate analysis...an important reference on the bookshelves of many scientific researchers and most practicing statisticians." ( Journal of the American Statistical Association , September 2004)
"...really well written. The edition will be certainly welcomed..." ( Zentralblatt Math , Vo.1039, No.08, 2004)

"...a wonderful textbook...that covers the mathematical theory of multivariate statistical analysis..." ( Clinical Chemistry , Vol. 50, No. 2, May 2004)

"...remains an authoritative work that can still be highly recommended..." ( Short Book Reviews , 2004)

"...still a very serious and comprehensive book on the statistical theory of multivariate analysis." ( Technometrics , Vol. 46, No. 1, February 2004)

"...remains a mathematically rigorous development of statistical methods for observations consisting of several measurements or characteristics of each subject and a study of their properties." ( Quarterly of Applied Mathematics , Vol. LXI, No. 4, December 2003)