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Introduction to multivariate statistical analysis / T.W. Anderson.

By: Material type: TextTextSeries: Wiley series in probability and statisticsPublication details: New Jersey : Wiley-Interscience, ©2003.Edition: 3rd edDescription: xx, 721 p. : ill. ; 25 cmISBN:
  • 9812530967
Subject(s): DDC classification:
  • 000SA.07  An551
Contents:
1. Introduction -- 2. The multivariate normal distribution -- 3. Estimation of the mean vector and the covariance matrix -- 4. The distributions and uses of sample correction coefficients -- 5. The generalized T2 statistics -- 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. Canonical correlations and canonical variables -- 13. The distributions of characteristic roots and vectors -- 14. Factor analysis -- 15. Patterns of dependence; graphical models -- Appendices -- References -- Index.
Summary: This updated and improved Third Edition familiarizes readers with these new advances, elucidating several aspects that are particularly relevant to methodology and comprehension. The Third Edition features new or more extensive coverage of: Patterns of Dependence and Graphical Models??"a new chapter Measures of correlation and tests of independence Reduced rank regression, including the limited-information maximum-likelihood estimator of an equation in a simultaneous equations model Elliptically contoured distributions Incorporation of the advice and comments of the readers of the first two editions as well as extensively classroom-tested techniques and calculations makes An Introduction to Multivariate Statistical Analysis, Third Edition, more valuable than ever for both professional statisticians and students of multivariate statistics.
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Includes bibliographical references and index.

1. Introduction --
2. The multivariate normal distribution --
3. Estimation of the mean vector and the covariance matrix --
4. The distributions and uses of sample correction coefficients --
5. The generalized T2 statistics --
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. Canonical correlations and canonical variables --
13. The distributions of characteristic roots and vectors --
14. Factor analysis --
15. Patterns of dependence; graphical models --
Appendices --
References --
Index.

This updated and improved Third Edition familiarizes readers with these new advances, elucidating several aspects that are particularly relevant to methodology and comprehension. The Third Edition features new or more extensive coverage of: Patterns of Dependence and Graphical Models??"a new chapter Measures of correlation and tests of independence Reduced rank regression, including the limited-information maximum-likelihood estimator of an equation in a simultaneous equations model Elliptically contoured distributions Incorporation of the advice and comments of the readers of the first two editions as well as extensively classroom-tested techniques and calculations makes An Introduction to Multivariate Statistical Analysis, Third Edition, more valuable than ever for both professional statisticians and students of multivariate statistics.

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