The Bootstrap and Edgeworth Expansion / Edition 1

The Bootstrap and Edgeworth Expansion / Edition 1

by Peter Hall
ISBN-10:
0387977201
ISBN-13:
9780387977201
Pub. Date:
01/09/1992
Publisher:
Springer New York
ISBN-10:
0387977201
ISBN-13:
9780387977201
Pub. Date:
01/09/1992
Publisher:
Springer New York
The Bootstrap and Edgeworth Expansion / Edition 1

The Bootstrap and Edgeworth Expansion / Edition 1

by Peter Hall
$139.99 Current price is , Original price is $139.99. You
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Overview

This monograph addresses two quite different topics, each being able to shed light on the other. Firstly, it lays the foundation for a particular view of the bootstrap. Secondly, it gives an account of Edgeworth expansion. The first two chapters deal with the bootstrap and Edgeworth expansion respectively, while chapters 3 and 4 bring these two themes together, using Edgeworth expansion to explore and develop the properties of the bootstrap. The book is aimed at graduate level for those with some exposure to the methods of theoretical statistics. However, technical details are delayed until the last chapter such that mathematically able readers without knowledge of the rigorous theory of probability will have no trouble understanding most of the book.

Product Details

ISBN-13: 9780387977201
Publisher: Springer New York
Publication date: 01/09/1992
Series: Springer Series in Statistics
Edition description: 1992
Pages: 354
Product dimensions: 6.10(w) x 9.25(h) x 0.03(d)

Table of Contents

1: Principles of Bootstrap Methodology.- 2: Principles of Edgeworth Expansion.- 3: An Edgeworth View of the Bootstrap.- 4: Bootstrap Curve Estimation.- 5: Details of Mathematical Rigour.- Appendix I: Number and Sizes of Atoms of Nonparametric Bootstrap Distribution.- Appendix II: Monte Carlo Simulation.- II.1 Introduction.- II.2 Uniform Resampling.- II.3 Linear Approximation.- II.4 Centring Method.- II.5 Balanced Resampling.- II.6 Antithetic Resampling.- II.7 Importance Resampling.- II.7.1 Introduction.- II.7.2 Concept of Importance Resampling.- II.7.3 Importance Resampling for Approximating Bias, Variance, Skewness, etc..- II.7.4 Importance Resampling for a Distribution Function.- II.8 Quantile Estimation.- Appendix III: Confidence Pictures.- Appendix IV: A Non-Standard Example: Quantite Error Estimation.- IV. 1 Introduction.- IV.2 Definition of the Mean Squared Error Estimate.- IV.3 Convergence Rate of the Mean Squared Error Estimate.- IV.4 Edgeworth Expansions for the Studentized Bootstrap Quantile Estimate.- Appendix V: A Non-Edgeworth View of the Bootstrap.- References.- Author Index.
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