Jackknife and Bootstrap

ISBN-10: 0387945156

ISBN-13: 9780387945156

Edition: 1995

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Description: The Jackknife and bootstrap are the most popular data-resampling methods used in statistical analysis. This book provides a systematic introduction to the theory of the jackknife, bootstrap and other resampling methods that have been developed in the last twenty years. It aims to provide a guide to using these methods which will enable applied statisticians to feel comfortable in applying them to data in their own research. The authors have included examples of applying these methods in various applications in both the independent and identically distributed (iid) case and in more complicated cases with non-iid data sets. Readers are assumed to have a reasonable knowledge of mathematical statistics and so this will be made suitable reading for graduate students, researchers and practitioners seeking a wide-ranging survey of this important area of statistical theory and application.

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Book details

Copyright year: 1995
Publisher: Springer
Publication date: 9/12/1996
Binding: Hardcover
Pages: 517
Size: 6.50" wide x 9.75" long x 1.25" tall
Weight: 1.936
Language: English

Preface
Introduction
Theory for the Jackknife
Theory for the Bootstrap
Bootstrap Confidence Sets and Hypothesis Tests
Computational Methods
Applications to Sample Surveys
Applications to Linear Models
Applications to Nonlinear, Nonparametric, and Multivariate Models
Applications to Time Series and Other Dependent Data
Bayesian Bootstrap and Random Weighting
Appendix A. Asymptotic Results
Appendix B. Notation
References
Author Index
Subject Index
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