When Does Bootstrap Work?

• Verfasst von: Mammen, Enno
• Titel: When Does Bootstrap Work?
• Titelzusatz: Asymptotic Results and Simulations
• Verf.angabe: by Enno Mammen
• Verlagsort: New York, NY
• Verlag: Springer New York
• Jahr: 1992
• Umfang: Online-Ressource (online resource)
• Gesamttitel/Reihe: Lecture Notes in Statistics ; 77
• Gesamttitel/Reihe: SpringerLink : Bücher
• Gesamttitel/Reihe: Springer eBook Collection : Mathematics and Statistics
• ISBN: 978-1-4612-2950-6
• DOI: doi:10.1007/978-1-4612-2950-6
• Schlagwörter: (s)Bootstrap-Statistik / (s)Asymptotik
• Datenträger: Online-Ressource
• Sprache: eng
• Bibliogr. Hinweis: Erscheint auch als : Druck-Ausgabe: Mammen, Enno, 1955 - : When does bootstrap work?. - New York : Springer, 1992. - VI, 196 S
• RVK-Notation: QH 230
• RVK-Notation: SI 856
• K10plus-PPN: 1655426141

Abstract

0. Introduction -- 1. Bootstrap and Asymptotic Normality -- 1. Introduction -- 2. Bootstrapping linear functionals. The i.i.d. case -- 3. Bootstrapping smooth functionals -- 4. Bootstrap and wild bootstrap in non i.i.d. models -- 5. Some simulations -- 6. Proofs -- Figures -- 2. An Example Where Bootstrap Fails: Comparing Nonparametric Versus Parametric Regression Fits -- 1. A goodness-of-fit test -- 2. How to bootstrap. Bootstrap and wild bootstrap -- 3. Proofs -- 3. A Bootstrap Success Story: Using Nonparametric Density Estimates in K-Sample Problems -- 1. Bootstrap tests -- 2. Bootstrap confidence regions -- 3. Proofs -- 4. A Bootstrap Test on the Number of Modes of a Density -- 1. Introduction -- 2. The number of modes of a kernel density estimator -- 3. Bootstrapping the test statistic -- 4. Proofs -- Figures -- 5. Higher-Order Accuracy of Bootstrap for Smooth Functionals -- 1. Introduction -- 2. Bootstrapping smooth functionals -- 3. Some more simulations. Bootstrapping an M-estimate -- 4. Proof of the theorem -- Figures -- 6. Bootstrapping Linear Models -- 1. Bootstrapping the least squares estimator -- 2. Bootstrapping F-tests -- 3. Proof of Theorem 3 -- 7. Bootstrapping Robust Regression -- 1. Introduction -- 2. Bootstrapping M-estimates -- 3. Stochastic expansions of M-estimates -- 4. Proofs -- Figures -- 8. Bootstrap and wild Bootstrap for High-Dimensional Linear Random Design Models -- 1. Introduction -- 2. Consistency of bootstrap for linear contrasts -- 3. Accuracy of the bootstrap -- 4. Bootstrapping F-tests -- 5. Proofs -- Tables -- Figures -- 9. References.