An introduction to the bootstrap
Author(s)
Bibliographic Information
An introduction to the bootstrap
（Monographs on statistics and applied probability, 57）
Chapman & Hall, c1993
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Graduate School of Asian and African Area Studies, Kyoto Universityアジア専攻
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Includes bibliographical references and indexes
Description and Table of Contents
Description
Statistics is a subject of many uses and surprisingly few effective practitioners. The traditional road to statistical knowledge is blocked, for most, by a formidable wall of mathematics. The approach in An Introduction to the Bootstrap avoids that wall. It arms scientists and engineers, as well as statisticians, with the computational techniques they need to analyze and understand complicated data sets.
Table of Contents
Introduction
The Accuracy of a Sample Mean
Random Samples and Probabilities
The Empirical Distribution Function and the Plug-In Principle
Standard Errors and Estimated Standard Errors
The Bootstrap Estimate of Standard Error
Bootstrap Standard Errors: Some Examples
More Complicated Data Structures
Regression Models
Estimates of Bias
The Jackknife
Confidence Intervals Based on Bootstrap "Tables"
Confidence Intervals Based on Bootstrap Percentiles
Better Bootstrap Confidence Intervals
Permutation Tests
Hypothesis Testing with the Bootstrap
Cross-Validation and Other Estimates of Prediction Error
Adaptive Estimation and Calibration
Assessing the Error in Bootstrap Estimates
A Geometrical Representation for the Bootstrap and Jackknife
An Overview of Nonparametric and Parametric Inference
Further Topics in Bootstrap Confidence Intervals
Efficient Bootstrap Computations
Approximate Likelihoods
Bootstrap Bioequivalence
Discussion and Further Topics
Appendix: Software for Bootstrap Computations
References
by "Nielsen BookData"