An Introduction to Bootstrap Methods with Applications to R
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… [Amazon.com]
Applied Mathematics | Applied Statistics | Computer Sciences | Statistical Methodology
Chernick, Michael R. and LaBudde, Robert A., "An Introduction to Bootstrap Methods with Applications to R" (2011). Mathematics & Statistics Faculty Books. 10.