An Introduction to Bootstrap Methods with Applications to R (eBook)

Michael R. Chernick, Robert A. LaBudde (Autoren)

eBook Download: PDF

2014 | 1. Auflage
240 Seiten
John Wiley & Sons (Verlag)
978-1-118-62545-3 (ISBN)

Infos

A comprehensive introduction to bootstrap methods in the R
programming environment



Bootstrap methods provide a powerful approach to statistical
data analysis, as they have more general applications than standard
parametric methods. An Introduction to Bootstrap Methods with
Applications to R explores the practicality of this approach and
successfully utilizes R to illustrate applications for the
bootstrap and other resampling methods. This book provides a modern
introduction to bootstrap methods for readers who do not have an
extensive background in advanced mathematics. Emphasis throughout
is on the use of bootstrap methods as an exploratory tool,
including its value in variable selection and other modeling
environments.

The authors begin with a description of bootstrap methods and
its relationship to other resampling methods, along with an
overview of the wide variety of applications of the approach.
Subsequent chapters offer coverage of improved confidence set
estimation, estimation of error rates in discriminant analysis, and
applications to a wide variety of hypothesis testing and estimation
problems, including pharmaceutical, genomics, and economics. To
inform readers on the limitations of the method, the book also
exhibits counterexamples to the consistency of bootstrap
methods.

An introduction to R programming provides the needed preparation
to work with the numerous exercises and applications presented
throughout the book. A related website houses the book's R
subroutines, and an extensive listing of references provides
resources for further study.

Discussing the topic at a remarkably practical and accessible
level, An Introduction to Bootstrap Methods with Applications to R
is an excellent book for introductory courses on bootstrap and
resampling methods at the upper-undergraduate and graduate levels.
It also serves as an insightful reference for practitioners working
with data in engineering, medicine, and the social sciences who
would like to acquire a basic understanding of bootstrap
methods.

Autor

MICHAEL R. CHERNICK, PhD, is Manager of Biostatistical Services at Lankenau Institute for Medical Research, where he conducts statistical design and analysis for pharmaceutical research. He has more than thirty years of experience in the application of statistical methods to such areas as medicine, energy, engineering, insurance, and pharmaceuticals. Dr. Chernick is the author of Bootstrap Methods: A Guide for Practitioners and Researchers, Second Edition and The Essentials of Biostatistics for Physicians, Nurses, and Clinicians, and the coauthor of Introductory Biostatistics for the Health Sciences: Modern Applications Including Bootstrap, all published by Wiley. ROBERT A. LaBUDDE, PhD, is President of Least Cost Formulations, Ltd., a mathematical software development company that specializes in optimization and process control software for manufacturing companies. He has extensive experience in industry and academia and currently serves as Adjunct Associate Professor in the Department of Mathematics and Statistics at Old Dominion University.

Rezensionen

"I recommend this text to anyone wishing to apply
computationally intensive methods and if you only purchase one book
on bootstrap methods then this could be the book for
you!." (International Statistical Review,
2012)

Produkt-Details

• Erscheint lt. Verlag: 21.8.2014
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Mathematik ► Statistik
• Themenwelt: Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik
• Themenwelt: Technik ► Elektrotechnik / Energietechnik
• Schlagworte: Angewandte Wahrscheinlichkeitsrechnung u. Statistik • Applied Probability & Statistics • Electrical & Electronics Engineering • Elektrotechnik u. Elektronik • Finanz- u. Wirtschaftsstatistik • Numerical Methods & Algorithms • Numerische Methoden u. Algorithmen • Statistics • Statistics for Finance, Business & Economics • Statistik • Stochastik
• ISBN-10: 1-118-62545-5 / 1118625455
• ISBN-13: 978-1-118-62545-3 / 9781118625453