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## Details

Genre/Form: | Electronic books |
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Additional Physical Format: | Print version: Davison, A. C. (Anthony Christopher). Bootstrap methods and their application. Cambridge ; New York, NY, USA : Cambridge University Press, 1997 (DLC) 96030064 (OCoLC)36130645 |

Material Type: | Document, Internet resource |

Document Type: | Internet Resource, Computer File |

All Authors / Contributors: |
A C Davison; D V Hinkley |

ISBN: | 9781107269903 1107269903 9781107263260 1107263263 9780511802843 0511802846 |

OCLC Number: | 880530770 |

Notes: | 6.2.6 Non-constant variance: weighted error resampling. |

Description: | 1 online resource (x, 582 pages) : illustrations. |

Contents: | Cover; Half-title; Title; Copyright; Contents; Preface; 1 Introduction; 2 The Basic Bootstraps; 2.1 Introduction; 2.1.1 Statistical functions; 2.1.2 Objectives; 2.2 Parametric Simulation; 2.2.1 Moment estimates; 2.2.2 Distribution and quantile estimates; 2.3 Nonparametric Simulation; 2.3.1 Comparison with parametric methods; 2.3.2 Effects of discreteness; 2.4 Simple Confidence Intervals; 2.5 Reducing Error; 2.5.1 Statistical error; 2.5.2 Simulation error; 2.6 Statistical Issues; 2.6.1 When does the bootstrap work?; 2.6.2 Rough statistics: unsmooth and unstable; 2.6.3 Conditional properties. 2.6.4 When might the bootstrap fail? 2.7 Nonparametric Approximations for Variance and Bias; 2.7.1 Delta methods; 2.7.2 Influence function and nonparametric delta method; 2.7.3 Jackknife estimates; 2.7.4 Empirical influence values via regression; 2.7.5 Variance estimates; 2.8 Subsampling Methods; 2.8.1 Jackknife methods; 2.8.2 All-subsamples method; 2.8.3 Half-sampling methods; 2.9 Bibliographic Notes; 2.10 Problems; 2.11 Practicals; 3 Further Ideas; 3.1 Introduction; 3.2 Several Samples; 3.2.1 Influence functions and variance approximations; 3.3 Semiparametric Models. 3.4 Smooth Estimates of F 3.5 Censoring; 3.5.1 Censored data; 3.5.2 Resampling plans; 3.6 Missing Data; 3.7 Finite Population Sampling; 3.8 Hierarchical Data; 3.9 Bootstrapping the Bootstrap; 3.9.1 Bias correction of bootstrap calculations; 3.9.2 Variation of properties of T; 3.10 Bootstrap Diagnostics; 3.10.1 Jackknife-after-bootstrap; 3.10.2 Linearity; 3.11 Choice of Estimator from the Data; 3.12 Bibliographic Notes; 3.13 Problems; 3.14 Practicals; 4 Tests; 4.1 Introduction; 4.2 Resampling for Parametric Tests; 4.2.1 Monte Carlo tests; 4.2.2 Markov chain Monte Carlo tests. 4.2.3 Parametric bootstrap tests 4.2.4 Graphical tests; 4.2.5 Choice of R; 4.3 Nonparametric Permutation Tests; 4.4 Nonparametric Bootstrap Tests; 4.4.1 Studentized bootstrap method; 4.4.2 Conditional bootstrap tests; 4.4.3 Multiple testing; 4.5 Adjusted P-values; 4.6 Estimating Properties of Tests; 4.7 Bibliographic Notes; 4.8 Problems; 4.9 Practicals; 5 Confidence Intervals; 5.1 Introduction; 5.2 Basic Confidence Limit Methods; 5.2.1 Parametric models; 5.2.2 Nonparametric models; 5.2.3 Choice of R; 5.3 Percentile Methods; 5.3.1 Basic percentile method; 5.3.2 Adjusted percentile method. 5.4 Theoretical Comparison of Methods 5.4.1 Second-order accuracy; 5.4.2 The ABC method; 5.5 Inversion of Significance Tests; 5.6 Double Bootstrap Methods; 5.7 Empirical Comparison of Bootstrap Methods; 5.8 Multiparameter Methods; 5.9 Conditional Confidence Regions; 5.10 Prediction; 5.11 Bibliographic Notes; 5.12 Problems; 5.13 Practicals; 6 Linear Regression; 6.1 Introduction; 6.2 Least Squares Linear Regression; 6.2.1 Regression fit and residuals; 6.2.2 Alternative models; 6.2.3 Resampling errors; 6.2.4 Resampling cases; 6.2.5 Significance tests for slope. |

Series Title: | Cambridge series on statistical and probabilistic mathematics. |

Responsibility: | A.C. Davison, D.V. Hinkley. |

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## Reviews

*Editorial reviews*

Publisher Synopsis

'... an extremely readable book. I would have no hestitation in recommending it as the most useful reference available for people wishing to learn or teach this subject. Certainly, this book is an essential addition to any library for those who use, or wish to use, bootstrap methodology.' Stephen Brooks, Royal Statistical Society Bulletin 'This book gives a broad and up-to-date coverage of bootstrap methods with numerous applied examples, together with the underlying general concepts developed in a coherent way.' L'Enseignment Mathematique 'Davison and Hinkley's book covers a remarkably broad range of bootstrap topics ... The authors have put considerable thought and time into their exposition. For learning how and when to bootstrap, there is no better start. Metrika ' ... this is a timely, comprehensive and well presented text on the bootstrap, which I recommend to statistical practitioners, researchers and students alike.' James Carpenter, London School of Hygiene and Tropical Medicine ' ... the authors provide a comprehensive and extremely readable overview of the current state of art in bootstrap methodology ... I strongly recommend this book ... this book should be part of your library.' Berwin A. Turlach, Journal of Applied Statistics '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, practitioners, and researchers alike.' Journal of American Statistical Association 'The coverage is comprehensive, making the book very useful ... The book is well written and is at a level which ensures its usefulness for a wide range of readers.' C. J. Field "...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 Read more...

*User-contributed reviews*