Happy holidays from us to you—get up to $30 off your next print or eBook! Shop now >>

Springer Texts in Statistics

Generalized Linear Models With Examples in R

Authors: Dunn, Peter, Smyth, Gordon

  • This book eases students into GLMs and demonstrates the need for GLMs by starting with regression
  • Shows how to implement the principles in R
  • Clearly written and logically structured to aid understanding
see more benefits

Buy this book

eBook $84.99
price for USA in USD (gross)
  • ISBN 978-1-4419-0118-7
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $109.99
price for USA in USD
  • ISBN 978-1-4419-0117-0
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this Textbook

This textbook presents an introduction to multiple linear regression, providing real-world data sets and practice problems. A practical working knowledge of applied statistical practice is developed through the use of these data sets and numerous case studies. The authors include a set of practice problems both at the end of each chapter and at the end of the book. Each example in the text is cross-referenced with the relevant data set, so that readers can load the data and follow the analysis in their own R sessions. The balance between theory and practice is evident in the list of problems, which vary in difficulty and purpose.


This book is designed with teaching and learning in mind, featuring chapter introductions and summaries, exercises, short answers, and simple, clear examples. Focusing on the connections between generalized linear models (GLMs) and linear regression, the book also references advanced topics and tools that have not typically been included in introductions to GLMs to date, such as Tweedie family distributions with power variance functions, saddlepoint approximations, likelihood score tests, modified profile likelihood, and randomized quantile residuals. In addition, the authors introduce the new R code package, GLMsData, created specifically for this book. Generalized Linear Models with Examples in R balances theory with practice, making it ideal for both introductory and graduate-level students who have a basic knowledge of matrix algebra, calculus, and statistics.  


About the authors

Peter K. Dunn is Associate Professor in the Faculty of Science, Health, Education and Engineering at the University of the Sunshine Coast. His work focuses on mathematical statistics, in particular generalized linear models. He has developed methods for accurate numerical evaluation of the densities of the Tweedie distributions, leading to a better understanding of these distributions. An engaging teacher, Dunn is the recipient of an Australian Office of Learning and Teaching citation. He has also won several conference paper prizes, including the EJ Pitman Prize at the Australian Statistics Conference.  He is a member of the Statistical Society of Australia Inc. and the Australian Mathematics Society. 

Gordon K. Smyth is Head of the Bioinformatics Division at the Walter and Eliza Hall Institute of Medical Research and Honorary Professor of Mathematics & Statistics at The University of Melbourne. He has published research on generalized linear models and statistical computing for over 30 years and is the author of several popular R packages. In recent years, he has particularly promoted the use of generalized linear models to model data from genomic sequencing technologies.

Table of contents (13 chapters)

  • Chapter 1: Statistical Models

    Dunn, Peter K. (et al.)

    Pages 1-30

  • Chapter 2: Linear Regression Models

    Dunn, Peter K. (et al.)

    Pages 31-91

  • Chapter 3: Linear Regression Models: Diagnostics and Model-Building

    Dunn, Peter K. (et al.)

    Pages 93-164

  • Chapter 4: Beyond Linear Regression: The Method of Maximum Likelihood

    Dunn, Peter K. (et al.)

    Pages 165-209

  • Chapter 5: Generalized Linear Models: Structure

    Dunn, Peter K. (et al.)

    Pages 211-241

Buy this book

eBook $84.99
price for USA in USD (gross)
  • ISBN 978-1-4419-0118-7
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $109.99
price for USA in USD
  • ISBN 978-1-4419-0117-0
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
Loading...

Recommended for you

Loading...

Bibliographic Information

Bibliographic Information
Book Title
Generalized Linear Models With Examples in R
Authors
Series Title
Springer Texts in Statistics
Copyright
2018
Publisher
Springer-Verlag New York
Copyright Holder
Springer Science+Business Media, LLC, part of Springer Nature
eBook ISBN
978-1-4419-0118-7
DOI
10.1007/978-1-4419-0118-7
Hardcover ISBN
978-1-4419-0117-0
Series ISSN
1431-875X
Edition Number
1
Number of Pages
XX, 562
Number of Illustrations
115 b/w illustrations
Topics