Multivariate Statistical Analysis: A High-Dimensional Approach (Hardcover, 2000)

Preface. Introduction. 1. Spectral Properties of Large Wishart Matrices. 2. Resolvents and Spectral Functions of Large Sample Covariance Matrices. 3. Resolvents and Spectral Functions of Large Pooled Sample Covariance Matrices. 4. Normal Evaluation of Quality Functions. 5. Estimation of High-Dimensional Inverse Covariance Matrices. 6. Epsilon-Dominating Component-Wise Shrinkage Estimators of Normal Mean. 7. Improved Estimators of High-Dimensional Expectation Vectors. 8. Quadratic Risk of Linear Regression with a Large Number of Random Predictors. 9. Linear Discriminant Analysis of Normal Populations with Coinciding Covariance Matrices. 10. Population Free Quality of Discrimination. 11. Theory of Discriminant Analysis of the Increasing Number of Independent Variables. Conclusions. References. Index.