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✦   LIBER   ✦

Bootstrap methods: a guide for practitioners and researchers

✍ Scribed by Michael R. Chernick


Book ID
127426167
Publisher
Wiley-Interscience
Year
2007
Tongue
English
Weight
2 MB
Series
Wiley Series in Probability and Statistics
Edition
2
Category
Library
ISBN
0470192569

No coin nor oath required. For personal study only.

✦ Synopsis


A practical and accessible introduction to the bootstrap methodβ€”β€”newly revised and updated

Over the past decade, the application of bootstrap methods to new areas of study has expanded, resulting in theoretical and applied advances across various fields. Bootstrap Methods, Second Edition is a highly approachable guide to the multidisciplinary, real-world uses of bootstrapping and is ideal for readers who have a professional interest in its methods, but are without an advanced background in mathematics.

Updated to reflect current techniques and the most up-to-date work on the topic, the Second Edition features:

  • The addition of a second, extended bibliography devoted solely to publications from 1999–2007, which is a valuable collection of references on the latest research in the field* A discussion of the new areas of applicability for bootstrap methods, including use in the pharmaceutical industry for estimating individual and population bioequivalence in clinical trials* A revised chapter on when and why bootstrap fails and remedies for 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 historical notes at the end of each chapter

With a strong focus on application, detailed explanations of methodology, and complete coverage of modern developments in the field, Bootstrap Methods, Second Edition is an indispensable reference for applied statisticians, engineers, scientists, clinicians, and other practitioners who regularly use statistical methods in research. It is also suitable as a supplementary text for courses in statistics and resampling methods at the upper-undergraduate and graduate levels.


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