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An introduction to multivariate statistical analysis T. W. Anderson

By: Anderson, Theodore WilburMaterial type: TextTextSeries: Wiley series in probability and mathematical statisticsPublication details: Hoboken, NJ [u.a.] Wiley 2003 Edition: 3. edDescription: XX, 721 S. : graph. DarstISBN: 0471360910Subject(s): Statistische Analyse | Multivariate AnalyseDDC classification: 519.535 Summary: 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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Holdings
Item type Current library Call number Status Date due Barcode Item holds
Monographie ausleihbar Monographie ausleihbar PIK
PIK M 311-08-0270 (Browse shelf(Opens below)) Checked out 29/09/2022 000579682
Total holds: 0

MAB0014.001: PIK M 311-08-0270

MAB0036: m

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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