You are not currently logged in.
Access JSTOR through your library or other institution:
If You Use a Screen ReaderThis content is available through Read Online (Free) program, which relies on page scans. Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Recent Developments in Bootstrap Methodology
A. C. Davison, D. V. Hinkley and G. A. Young
Vol. 18, No. 2, Silver Anniversary of the Bootstrap (May, 2003), pp. 141-157
Published by: Institute of Mathematical Statistics
Stable URL: http://www.jstor.org/stable/3182844
Page Count: 17
You can always find the topics here!Topics: Statism, Estimators, Statistics, Bootstrap resampling, Approximation, Inference, Confidence interval, Null hypothesis, Statistical estimation, Simulations
Were these topics helpful?See something inaccurate? Let us know!
Select the topics that are inaccurate.
Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
Preview not available
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.
Statistical Science © 2003 Institute of Mathematical Statistics