Reminiscences, and some explorations about the bootstrap

DOI10.1016/j.spa.2016.04.016zbMath1387.60007OpenAlexW2343794847MaRDI QIDQ335633

Richard M. Dudley

Publication date: 2 November 2016

Published in: Stochastic Processes and their Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spa.2016.04.016

zbMATH Keywords

confidence intervalsbias-correctionempirical measures

Mathematics Subject Classification ID

Central limit and other weak theorems (60F05) Bootstrap, jackknife and other resampling methods (62F40) Functional limit theorems; invariance principles (60F17) Research exposition (monographs, survey articles) pertaining to probability theory (60-02) History of probability theory (60-03)

Uses Software

• R
• MASS (R)
• bootstrap
• bootlib

Cites Work

• Some limit theorems for empirical processes (with discussion)
• Gaussian characterization of uniform Donsker classes of functions
• Bootstrapping general empirical measures
• Bootstrap methods for standard errors, confidence intervals, and other measures of statistical accuracy
• Bootstrap of the mean in the infinite variance case
• Hungarian constructions from the nonasymptotic viewpoint
• Necessary conditions for the bootstrap of the mean
• Some asymptotic theory for the bootstrap
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• The law of large numbers and the central limit theorem in Banach spaces
• Bootstrap methods: another look at the jackknife
• Bootstrap by sequential resampling
• Bootstrap confidence intervals. With comments and a rejoinder by the authors
• The jackknife and bootstrap
• Weak convergence and empirical processes. With applications to statistics
• Statistical Analysis of Financial Data in S-Plus
• Lower bounds on the approximation of the multivariate empirical process
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• A comparison of bootstrap method and Edgeworth expansion in approximating the distribution of sample variance — one sample and two sample cases
• Uniform Central Limit Theorems
• Distances of Probability Measures and Random Variables
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• On the Asymptotic Distribution of Differentiable Statistical Functions
• Convergence de la répartition empirique vers la répartition théorique
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