An introduction to multivariate statistical analysis
著者
書誌事項
An introduction to multivariate statistical analysis
（Wiley series in probability and mathematical statistics）
Wiley-Interscience, c2003
3rd ed
- : cloth
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注記
Includes bibliographical references (p. 687-711) and index
内容説明・目次
内容説明
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.
目次
- 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.
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