A Practitioner's Guide to Resampling for Data Analysis, Data Mining, and Modeling

Resampling methods techniques for repeatedly resampling data to obtain results are being used in virtually every research area. This practical guide discusses the applications of these methods, especially in the areas of microarrays and data mining. Each chapter contains a wealth of exercises along with R and Stata code. Written by a leading authority in the field, the text covers such topics as estimation, the bootstrap method, multivariate tests, decision trees, categorical data, multiple hypotheses, and model building.