When Does Bootstrap Work?: Asymptotic Results and Simulations

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 Boo...

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Bibliographische Detailangaben
1. Verfasser: Mammen, Enno (VerfasserIn)
Dokumenttyp: Buch/Monographie
Sprache:Englisch
Veröffentlicht: New York, NY Springer New York 1992
Schriftenreihe:Lecture Notes in Statistics 77
SpringerLink Bücher
Springer eBook Collection Mathematics and Statistics
DOI:10.1007/978-1-4612-2950-6
Schlagworte:
Online-Zugang:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1007/978-1-4612-2950-6
Verlag, Zentralblatt MATH, Inhaltstext: https://zbmath.org/?q=an:0760.62038
Volltext
Verfasserangaben:by Enno Mammen
Beschreibung
Zusammenfassung: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.
Beschreibung:Online Resource
ISBN:9781461229506
DOI:10.1007/978-1-4612-2950-6