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Other titles in the Cambridge Series in Statistical and Probabilistic Mathematic series:
Bootstrap Methods and Their Applicationby A. C. Davison
Synopses & Reviews
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.
A statistical methods book, with code on supporting website.
Bootstrap methods enable fairly sophisticated statistical calculations to be done by computer simulation. The range of application is broad: from biology and medicine through to econometrics and finance. Compared with other treatments, applications are thoroughly covered here, with an emphasis on practical implementation (computer algorithms are clearly described, and computer code is available on the supporting website).
The recently-developed Bootstrap methods enable fairly sophisticated statistical calculations to be done by computer simulation. This frees the application of both elementary and advanced statistical methods from unreliable mathematical formulae, and makes them more generally applicable. The range of application is very wide; from epidemiology, biology and medicine through to econometrics and finance. In comparison with other books on the subject, here this variety of applications is covered much more thoroughly with a strong emphasis on practical implementation (computer algorithms are clearly described, and computer code is available on the supporting website).
Statistical methods book, with code on supporting website.
Statistical methods book, including programs on disk.
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.
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