Bootstrap Methods

• Date de parution : 23/09/2011
• Editeur : Wiley-interscience
• EAN : 9781118211595
• Série : (-)
• Support : Livre numérique

• Nombre de pages : (-)
• Collection : (-)
• Genre : (-)
• Thème : Non attribué
• Prix littéraire(s) : (-)

A practical and accessible introduction to the bootstrap methodnewly revised and updatedOver 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... Voir plus

A practical and accessible introduction to the bootstrap methodnewly revised and updatedOver 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 19992007, which is a valuable collection of references on the latest research in the fieldA discussion of the new areas of applicability for bootstrap methods, including use in the pharmaceutical industry for estimating individual and population bioequivalence in clinical trialsA revised chapter on when and why bootstrap fails and remedies for overcoming these drawbacksAdded coverage on regression, censored data applications, P-value adjustment, ratio estimators, and missing dataNew examples and illustrations as well as extensive historical notes at the end of each chapterWith 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.