SIAM Homepage | Search Catalog | New Books | Author Index | Series Index | Title Index | View My Shopping Cart

The catalog and shopping cart are hosted for SIAM by EasyCart. Your transaction is secure. If you have any questions about your order, contact

Purchase Now!

The Jackknife, the Bootstrap, and Other Resampling Plans

Bradley Efron

CBMS-NSF Regional Conference Series in Applied Mathematics 38

The jackknife and the bootstrap are nonparametric methods for assessing the errors in a statistical estimation problem. They provide several advantages over the traditional parametric approach: the methods are easy to describe and they apply to arbitrarily complicated situations; distribution assumptions, such as normality, are never made.

This monograph connects the jackknife, the bootstrap, and many other related ideas such as cross-validation, random subsampling, and balanced repeated replications into a unified exposition. The theoretical development is at an easy mathematical level and is supplemented by a large number of numerical examples.

The methods described in this monograph form a useful set of tools for the applied statistician. They are particularly useful in problem areas where complicated data structures are common, for example, in censoring, missing data, and highly multivariate situations.


The Jackknife Estimate of Bias; The Jackknife Estimate of Variance; Bias of the Jackknife Variance Estimate; The Bootstrap; The Infinitesimal Jackknife; The Delta Method and the Influence Function; Cross-Validation, Jackknife and Bootstrap; Balanced Repeated Replications (Half-Sampling); Random Subsampling; Nonparametric Confidence Intervals.

1982 / vii + 92 pages / Softcover / ISBN-13: 978-0-898711-79-0 / ISBN-10: 0-89871-179-7 /
List Price $48.00 / SIAM/CBMS Member Price $33.60 / Order Code CB38
Quantity desired

Search our catalog for:

Shopping cart provided by:
Select quantity and list or member price and then click the "Click to Order" button to add books to your shopping cart.
Banner art adapted from a figure by Hinke M. Osinga and Bernd Krauskopf (University of Auckland, NZ.)