Bootstrap Methods and their Application
Bootstrap Methods and their Application
D. V. Hinkley, University of California, Santa Barbara
$110.00
USDBootstrap methods are computer-intensive methods of statistical analysis, which use simulation to calculate standard errors, confidence intervals, and significance tests. The methods apply for any level of modelling, and so can be used for fully parametric, semiparametric, and completely nonparametric analysis. This 1997 book gives a broad and up-to-date coverage of bootstrap methods, with numerous applied examples, developed in a coherent way with the necessary theoretical basis. Applications include stratified data; finite populations; censored and missing data; linear, nonlinear, and smooth regression models; classification; time series and spatial problems. Special features of the book include: extensive discussion of significance tests and confidence intervals; material on various diagnostic methods; and methods for efficient computation, including improved Monte Carlo simulation. Each chapter includes both practical and theoretical exercises. S-Plus programs for implementing the methods described in the text are available from the supporting website.
- First book aimed at users
- S-Plus programs for data analysis available from http://statwww.epfl.ch/davison/BMA/
- Class tested
Reviews & endorsements
"...well-illustrated examples..." Sociological Methods and Research
"The number and diversity of examples greatly enhance the understanding of the text. We marvel at the number of resamples that were taken in support of the book! The authors use hundreds of plots and dozens of tables to demonstrate and evaluate the uses of bootstrap... Statisticians with little or no familiarity with the bootstrap will find Bootstrap Methods and Their Application to be a thorough introduction to its use in solving real-world problems...We recommend this book most highly. It made us stop and think regularly and contributed tremendously to our understanding of the bootstrap. It is an excellent book for professors, students, practicioners, and researchers alike." Thomas Loughin and Christopher R. Bilder, Journal of the American Statistical Association
"...a comprehensive and extremely readable overview of the current state of art in bootstrap methodology. Through the numerous exercises, practicals and examples the reader obtains a good understanding for the strength of bootstrap methods, the problems for which they work and how to avoid their pitfalls. I strongly recommend this book to anybody who uses, or wishes to use, bootstrap methods...this book should be part of your library." The University of Adelaide
"The authors have done an excellent job of mixing up the theory and the applications of bootstrap...Every applied statistician who wants to apply bootstrap with some knowledge of the underlined theory so that it is not applied improperly should take a look at this book." Technometrics
Product details
January 2014Adobe eBook Reader
9781107266384
0 pages
0kg
120 b/w illus. 70 tables 200 exercises
This ISBN is for an eBook version which is distributed on our behalf by a third party.
Table of Contents
- 1. Introduction
- 2. The basic bootstraps
- 3. Further ideas
- 4. Tests
- 5. Confidence intervals
- 6. Regression models
- 7. Further topics in regression
- 8. Complex dependence
- 9. Improved calculation
- 10. Semiparametric likelihood inference
- 11. Computer implementation
- Appendix
- Cumulant calculations
- Bibliography
- Index.
