Chernick Bootstrap Methods

A Guide for Practitioners and Researchers
2. Auflage 2011
ISBN: 978-1-118-21159-5
Verlag: John Wiley & Sons
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 400 Seiten, E-Book

Reihe: Wiley Series in Probability and Statistics

A practical and accessible introduction to the bootstrapmethod----newly revised and updated
Over the past decade, the application of bootstrap methods tonew areas of study has expanded, resulting in theoretical andapplied advances across various fields. Bootstrap Methods,Second Edition is a highly approachable guide to themultidisciplinary, real-world uses of bootstrapping and is idealfor readers who have a professional interest in its methods, butare without an advanced background in mathematics.
Updated to reflect current techniques and the most up-to-datework on the topic, the Second Edition features:
* The addition of a second, extended bibliography devoted solelyto publications from 1999-2007, which is a valuablecollection of references on the latest research in the field
* A discussion of the new areas of applicability for bootstrapmethods, including use in the pharmaceutical industry forestimating individual and population bioequivalence in clinicaltrials
* A revised chapter on when and why bootstrap fails and remediesfor overcoming these drawbacks
* Added coverage on regression, censored data applications,P-value adjustment, ratio estimators, and missing data
* New examples and illustrations as well as extensive historicalnotes at the end of each chapter
With a strong focus on application, detailed explanations ofmethodology, and complete coverage of modern developments in thefield, Bootstrap Methods, Second Edition is an indispensablereference for applied statisticians, engineers, scientists,clinicians, and other practitioners who regularly use statisticalmethods in research. It is also suitable as a supplementary textfor courses in statistics and resampling methods at theupper-undergraduate and graduate levels.

Autoren/Hrsg.

Chernick, Michael R.

Inhaltsverzeichnis

Preface to Second Edition.
Preface to First Edition.
Acknowledgments.
1. What Is Bootstrapping?
1.1. Background.
1.2. Introduction.
1.3. Wide Range of Applications.
1.4. Historical Notes.
1.5. Summary.
2. Estimation.
2.1. Estimating Bias.
2.2. Estimating Location and Dispersion.
2.3. Historical Notes.
3. Confi dence Sets and Hypothesis Testing.
3.1. Confi dence Sets.
3.2. Relationship Between Confi dence Intervals and Tests ofHypotheses.
3.3. Hypothesis Testing Problems.
3.4. An Application of Bootstrap Confi dence Intervals to BinaryDose-Response Modeling.
3.5. Historical Notes.
4. Regression Analysis.
4.1. Linear Models.
4.2. Nonlinear Models.
4.3. Nonparametric Models.
4.4. Historical Notes.
5. Forecasting and Time Series Analysis.
5.1. Methods of Forecasting.
5.2. Time Series Models.
5.3. When Does Bootstrapping Help with Prediction Intervals?
5.4. Model-Based Versus Block Resampling.
5.5. Explosive Autoregressive Processes.
5.6. Bootstrapping-Stationary Arma Models.
5.7. Frequency-Based Approaches.
5.8. Sieve Bootstrap.
5.9. Historical Notes.
6. Which Resampling Method Should You Use?
6.1. Related Methods.
6.2. Bootstrap Variants.
7. Effi cient and Effective Simulation.
7.1. How Many Replications?
7.2. Variance Reduction Methods.
7.3. When Can Monte Carlo Be Avoided?
7.4. Historical Notes.
8. Special Topics.
8.1. Spatial Data.
8.2. Subset Selection.
8.3. Determining the Number of Distributions in a MixtureModel.
8.4. Censored Data.
8.5. p-Value Adjustment.
8.6. Bioequivalence Applications.
8.7. Process Capability Indices.
8.8. Missing Data.
8.9. Point Processes.
8.10. Lattice Variables.
8.11. Historical Notes.
9. When Bootstrapping Fails Along with Remedies forFailures.
9.1. Too Small of a Sample Size.
9.2. Distributions with Infi nite Moments.
9.3. Estimating Extreme Values.
9.4. Survey Sampling.
9.5. Data Sequences that Are M-Dependent.
9.6. Unstable Autoregressive Processes.
9.7. Long-Range Dependence.
9.8. Bootstrap Diagnostics.
9.9. Historical Notes.
Bibliography 1 (Prior to 1999).
Bibliography 2 (1999-2007).
Author Index.
Subject Index.

Über Autor(innen)

Michael R. Chernick, PhD, is Principal Senior Statistician at United BioSource Corporation, providing statistical design and analysis for pharmaceutical research on a variety of diseases, including a recent emphasis on oncology. He has over twenty years of experience in the application of statistical methods to the pharmaceutical industry as well as to medical devices, energy data, engineering problems, and insurance data. His research interests include extreme value theory, outliers, data editing, time series, and bootstrap methods. Dr. Chernick is also the coauthor of Introductory Biostatistics for the Health Sciences (Wiley).