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Weak Convergence and Empirical Processes: With Applications to Statistics (Springer Series in Statistics) by Vaart, Aad W. van der.; Wellner, Jon A is a nonfiction available to read on EtoBox.

What is Weak Convergence and Empirical Processes: With Applications to Statistics (Springer Series in Statistics) about?

1.1. Introduction -- 1.2. Outer Integrals and Measurable Majorants -- 1.3. Weak Convergence -- 1.4. Product Spaces -- 1.5. Spaces of Bounded Functions -- 1.6. Spaces of Locally Bounded Functions -- 1.7. The Ball Sigma-Field and Measurability of Suprema -- 1.8. Hilbert Spaces -- 1.9. Convergence: Almost Surely and in Probability -- 1.10. Convergence: Weak, Almost Uniform, and in Probability -- 1.11. Refinements -- 1.12. Uniformity and Metrization -- 2.1. Introduction -- 2.2. Maximal Inequalities and Covering Numbers -- 2.3. Symmetrization and Measurability -- 2.4. Glivenko-Cantelli Theorems -- 2.5. Donsker Theorems -- 2.6. Uniform Entropy Numbers -- 2.7. Bracketing Numbers -- 2.8. Uniformity in the Underlying Distribution -- 2.9. Multiplier Central Limit Theorems -- 2.10. Permanence of the Donsker Property -- 2.11. The Central Limit Theorem for Processes -- 2.12. Partial-Sum Processes -- 2.13. Other Donsker Classes -- 2.14. Tail Bounds -- 3.1. Introduction -- 3.2. M-Estimators -- 3.3. Z-Estimators -- 3.4. Rates of Convergence -- 3.5. Random Sample Size, Poissonization and Kac Processes -- 3.6. The Bootstrap -- 3.7. The Two-Sample Problem -- 3.8. Independence Empirical Processes -- 3

Who reads Weak Convergence and Empirical Processes: With Applications to Statistics (Springer Series in Statistics)?

Author

Vaart, Aad W. van der.; Wellner, Jon A

Publisher

Springer New York : Imprint : Springer

Published

1996

Language

EN

ISBN

9781475725452

Category

nonfiction

Subjects

Mathematics, Stem