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{1063994969,
author = {Davison, A. C. and Hinkley, D. V. and Young, G. A.},
title = {Recent Developments in Bootstrap Methodology},
journal = {Statist. Sci.},
volume = {18},
number = {1},
year = {2003},
pages = { 141-157},
language = {en},
url = {http://dml.mathdoc.fr/item/1063994969}
}
Davison, A. C.; Hinkley, D. V.; Young, G. A. Recent Developments in Bootstrap Methodology. Statist. Sci., Tome 18 (2003) no. 1, pp. 141-157. http://gdmltest.u-ga.fr/item/1063994969/