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Bootstrap Methods and their Application (Cambridge Series in Statistical and Probabilistic Mathematics), by A. C. Davison, D. V. Hinkley
Free Ebook Bootstrap Methods and their Application (Cambridge Series in Statistical and Probabilistic Mathematics), by A. C. Davison, D. V. Hinkley
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This 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. Included with the book is a disk of purpose-written S-Plus programs for implementing the methods described in the text. Computer algorithms are clearly described, and computer code is included on a 3-inch, 1.4M disk for use with IBM computers and compatible machines. Users must have the S-Plus computer application. Author resource page: http://statwww.epfl.ch/davison/BMA/
- Sales Rank: #140234 in Books
- Brand: Cambridge University Press
- Published on: 1997-10-28
- Ingredients: Example Ingredients
- Original language: English
- Number of items: 1
- Dimensions: 9.96" h x 1.22" w x 6.97" l, 2.20 pounds
- Binding: Paperback
- 594 pages
- Used Book in Good Condition
Review
"...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
Most helpful customer reviews
15 of 15 people found the following review helpful.
A Clear Introduction to the Bootstrap & Applications
By C. Andersen
This is a well-written book, and I had the basic bootstrap notion figured-out and implemented within a few days, though it will be some time before I develop any serious depth of mastery of the material. For those unfamiliar with the bootstrap method, by a system of resampling from an existing sample of data it provides a means of establishing the standard error for pretty-near any statistical measure (like the standard error of the mean in traditional statistics), as well as the determination of general confidence intervals for those measures, even when the distribution of the data is non-gaussian or unknown. I do find the author's symbolic notation a bit confusing - perhaps TOO compact, and many of the symbolic expressions would really benefit from an associated clearly written paraphrasing (difficult for me to remember all the conventions after putting the book down for a few days). Still, to go from being barely aware of the technique to applying it to the data analysis in a current research project over a period of several weeks suggests that this text does a heck of a good job at conveying the intended introduction.
3 of 23 people found the following review helpful.
Book has my vote
By Paul Nicholas
Relevant and clear in explanations throughout.
9 of 9 people found the following review helpful.
It is a very good book
By C. Tu
People might have many different reasons to use bootstrap techniques and they might have various backgrounds therefore this is a good book for readers that want to learn the bootstrap. If you do not have strong background in statistics then the practicals section will help you to programm and analyze the data. If you have background this book does show you the theory behind.
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