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About this book
The jackknife and bootstrap are the most popular data-resampling meth ods used in statistical analysis. The resampling methods replace theoreti cal derivations required in applying traditional methods (such as substitu tion and linearization) in statistical analysis by repeatedly resampling the original data and making inferences from the resamples. Because of the availability of inexpensive and fast computing, these computer-intensive methods have caught on very rapidly in recent years and are particularly appreciated by applied statisticians. The primary aims of this book are (1) to provide a systematic introduction to the theory of the jackknife, the bootstrap, and other resampling methods developed in the last twenty years; (2) to provide a guide for applied statisticians: practitioners often use (or misuse) the resampling methods in situations where no theoretical confirmation has been made; and (3) to stimulate the use of the jackknife and bootstrap and further devel opments of the resampling methods. The theoretical properties of the jackknife and bootstrap methods are studied in this book in an asymptotic framework. Theorems are illustrated by examples. Finite sample properties of the jackknife and bootstrap are mostly investigated by examples and/or empirical simulation studies. In addition to the theory for the jackknife and bootstrap methods in problems with independent and identically distributed (Li.d.) data, we try to cover, as much as we can, the applications of the jackknife and bootstrap in various complicated non-Li.d. data problems.
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Table of contents (10 chapters)
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Front Matter
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Back Matter
Authors and Affiliations
Bibliographic Information
Book Title: The Jackknife and Bootstrap
Authors: Jun Shao, Dongsheng Tu
Series Title: Springer Series in Statistics
DOI: https://doi.org/10.1007/978-1-4612-0795-5
Publisher: Springer New York, NY
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eBook Packages: Springer Book Archive
Copyright Information: Springer Science+Business Media New York 1995
Hardcover ISBN: 978-0-387-94515-6Published: 21 July 1995
Softcover ISBN: 978-1-4612-6903-8Published: 04 October 2012
eBook ISBN: 978-1-4612-0795-5Published: 06 December 2012
Series ISSN: 0172-7397
Series E-ISSN: 2197-568X
Edition Number: 1
Number of Pages: XVII, 517
Topics: Applications of Mathematics