An introduction to multivariate statistical analysis T. W. Anderson
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PIK | PIK M 311-08-0270 (Browse shelf(Opens below)) | Checked out | 02/02/2023 | 000579682 |
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PIK M 311-08-0264 Intelligent data analysis | PIK M 311-08-0267 Independent component analysis | PIK M 311-08-0268 Experts in uncertainty | PIK M 311-08-0270 An introduction to multivariate statistical analysis | PIK M 311-09-0003 Irreversible decisions under uncertainty | PIK M 311-09-0009 Introduction to spectral analysis | PIK M 311-09-0010 Random matrices |
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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 Correlation Coefficients.5. The Generalized T^2-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 Variance9. 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.
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