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Bootstrap Methods and their Application (Cambridge Series in Statistical and Probabilistic Mathematics) 1st Edition

4.4 out of 5 stars 9 customer reviews
ISBN-13: 978-0521574716
ISBN-10: 0521574714
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Frequently Bought Together

  • Bootstrap Methods and their Application (Cambridge Series in Statistical and Probabilistic Mathematics)
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  • An Introduction to the Bootstrap (Chapman & Hall/CRC Monographs on Statistics & Applied Probability)
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  • Large-Scale Inference: Empirical Bayes Methods for Estimation, Testing, and Prediction (Institute of Mathematical Statistics Monographs)
Total price: $229.54
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Editorial Reviews

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

Book Description

The bootstrap technique is a powerful and modern tool used in the analysis of statistical data. This book is the first that is aimed at users of the method. It describes many examples, and includes programs in S-plus, available on a disk supplied with the book, for practical use.
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Product Details

  • Series: Cambridge Series in Statistical and Probabilistic Mathematics (Book 1)
  • Paperback: 594 pages
  • Publisher: Cambridge University Press; 1 edition (October 28, 1997)
  • Language: English
  • ISBN-10: 0521574714
  • ISBN-13: 978-0521574716
  • Product Dimensions: 7 x 1.2 x 10 inches
  • Shipping Weight: 2.7 pounds (View shipping rates and policies)
  • Average Customer Review: 4.4 out of 5 stars  See all reviews (9 customer reviews)
  • Amazon Best Sellers Rank: #469,213 in Books (See Top 100 in Books)

Customer Reviews

Top Customer Reviews

By C. Andersen on August 25, 2007
Format: Paperback Verified Purchase
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.
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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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Format: Paperback
This book is loaded with good text book examples and covers a wide variety of bootstrap applications. It is great as a reference book on the bootstrap or as a course text at a graduate level. Chernick (1999) is a little more up-to-date and covers the classifcation error rate estimation problem that is not addressed in this text. Chernick (1999) also has many more references. Efron and Tibshirani (1993) is another fine text that is a little more intuition based with less mathematics. Fieller's problem with ratio estimation and some other gems are well covered in Efron and Tibshirani but not here. Davison and Hinkley do the best job on time series of any of the bootstrap books with details about moving block bootstrap and some interesting applications. The second edition of my text Chernick (2007) just came out and is far more up to date with an improved treatment of time series. But Davison and Hinkley is still by far the best book for a course because of the many exercises and practicals.
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I think that the book could be made easier to read. At least for me, I didn't get the bootstrap principle by reading this book, until I read the Russian matryoshka doll example on page 4 of Hall (1992). The concept of bootstrap is simple and general (it doesn't matter whether it is parametric or non-parametric). However, the introduction in Chap 2 of Davison's book makes the basic principle harder to get if one does't know it already.

Another comment is that, although there is a R package boot, most examples used the book are not available in the package. It will be helpful to the readers in learning how the method is used in practice by disclosing all the code for running the examples in the book.
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Books as complicated as this are not written for novices. But some at least try to explain something, some ideas. at least in introduction. This one doesn't try. It is written for those who knows, for a narrow circle. I have a feeling, that it is deliberately written less clearly than possible, to show how smart the author is. Or maybe they don't care.
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