Recent Developments in Bootstrap Methodology
A. C. Davison, D. V. Hinkley, and G. A. Young
Source: Statist. Sci. Volume 18, Issue 2
(2003), 141-157.
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.
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Keywords: Bagging; bootstrap; conditional inference; empirical strength probability; parametric bootstrap; subsampling; superefficient estimator; tilted distribution; time series; weighted bootstrap
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