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  • © 2021

Bootstrap Methods

With Applications in R

  • Presents a concise introduction to bootstrap methods
  • Includes implementations of the algorithms in R, focusing on comprehensibility
  • Emphasizes goodness-of-fit tests
  • Provides complete proofs for those interested in theory and various applications for those interested in practice
  • Includes supplementary material: sn.pub/extras

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Table of contents (6 chapters)

  1. Front Matter

    Pages i-xvi
  2. Introduction

    • Gerhard Dikta, Marsel Scheer
    Pages 1-7
  3. Generating Random Numbers

    • Gerhard Dikta, Marsel Scheer
    Pages 9-20
  4. The Classical Bootstrap

    • Gerhard Dikta, Marsel Scheer
    Pages 21-45
  5. Bootstrap-Based Tests

    • Gerhard Dikta, Marsel Scheer
    Pages 47-72
  6. Regression Analysis

    • Gerhard Dikta, Marsel Scheer
    Pages 73-164
  7. Goodness-of-Fit Test for Generalized Linear Models

    • Gerhard Dikta, Marsel Scheer
    Pages 165-230
  8. Back Matter

    Pages 231-256

About this book

This book provides a compact introduction to the bootstrap method. In addition to classical results on point estimation and test theory, multivariate linear regression models and generalized linear models are covered in detail. Special attention is given to the use of bootstrap procedures to perform goodness-of-fit tests to validate model or distributional assumptions. In some cases, new methods are presented here for the first time.

The text is motivated by practical examples and the implementations of the corresponding algorithms are always given directly in R in a comprehensible form. Overall, R is given great importance throughout. Each chapter includes a section of exercises and, for the more mathematically inclined readers, concludes with rigorous proofs. The intended audience is graduate students who already have a prior knowledge of probability theory and mathematical statistics.


Authors and Affiliations

  • Department of Medical Engineering and Technomathemathics, FH Aachen – University of Applied Sciences, Jülich, Germany

    Gerhard Dikta

  • Bayer AG, Cologne, Germany

    Marsel Scheer

About the authors

Gerhard Dikta has been a full-time professor at the Department of Medical Engineering and Technomathematics within the University of Applied Sciences, FH-Aachen, since 1993. He has also been an adjunct professor at the Department of Mathematics of the University of Wisconsin-Milwaukee since 2004. In addition to general problems in mathematical statistics, statistical modeling, simulation and optimization, his research interests and contributions are in survival analysis and, recently, in the development of statistical test methods for model verification.

Marsel Scheer has been a data scientist at Bayer AG since 2019. He was head of biostatistics and software development at Myriad International GmbH (formerly Sividon Diagnostics GmbH) for 5 years and worked as a biometrician in diabetes research at the German Diabetes Center for 6 years. His research interests are in statistical learning and modeling, machine learning, simulation and software development.


Bibliographic Information

Buy it now

Buying options

eBook USD 69.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 89.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 119.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access