Statistical Science

Recent Developments in Bootstrap Methodology

A. C. Davison, D. V. Hinkley, and G. A. Young

Full-text: Open access

Abstract

Ever since its introduction, the bootstrap has provided both a powerful set of solutions for practical statisticians, and a rich source of theoretical and methodological problems for statistics. In this article, some recent developments in bootstrap methodology are reviewed and discussed. After a brief introduction to the bootstrap, we consider the following topics at varying levels of detail: the use of bootstrapping for highly accurate parametric inference; theoretical properties of nonparametric bootstrapping with unequal probabilities; subsampling and the m out of n bootstrap; bootstrap failures and remedies for superefficient estimators; recent topics in significance testing; bootstrap improvements of unstable classifiers and resampling for dependent data. The treatment is telegraphic rather than exhaustive.

Article information

Source
Statist. Sci. Volume 18, Issue 2 (2003), 141-157.

Dates
First available in Project Euclid: 19 September 2003

Permanent link to this document
https://projecteuclid.org/euclid.ss/1063994969

Digital Object Identifier
doi:10.1214/ss/1063994969

Mathematical Reviews number (MathSciNet)
MR2026076

Zentralblatt MATH identifier
1331.62179

Keywords
Bagging bootstrap conditional inference empirical strength probability parametric bootstrap subsampling superefficient estimator tilted distribution time series weighted bootstrap

Citation

Davison, A. C.; Hinkley, D. V.; Young, G. A. Recent Developments in Bootstrap Methodology. Statist. Sci. 18 (2003), no. 2, 141--157. doi:10.1214/ss/1063994969. https://projecteuclid.org/euclid.ss/1063994969


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