Linear Regression

Authors: Olive, David

  • R functions are available for download from author's website
  • Includes an extensive bibliography
  • Problems are provided at the end of every chapter
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eBook $69.99
price for USA (gross)
  • ISBN 978-3-319-55252-1
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $89.99
price for USA
  • Customers within the U.S. and Canada please contact Customer Service at 1-800-777-4643, Latin America please contact us at +1-212-460-1500 (Weekdays 8:30am – 5:30pm ET) to place your order.
  • Due: May 17, 2017
  • ISBN 978-3-319-55250-7
  • Free shipping for individuals worldwide
About this Textbook

This text covers both multiple linear regression and some experimental design models. The text uses the response plot to visualize the model and to detect outliers, does not assume that the error distribution has a known parametric distribution, develops prediction intervals that work when the error distribution is unknown, suggests bootstrap hypothesis tests that may be useful for inference after variable selection, and develops prediction regions and large sample theory for the multivariate linear regression model that has m response variables. A relationship between multivariate prediction regions and confidence regions provides a simple way to bootstrap confidence regions. These confidence regions often provide a practical method for testing hypotheses. There is also a chapter on generalized linear models and generalized additive models.

There are many R functions to produce response and residual plots, to simulate prediction intervals and hypothesis tests, to detect outliers, and to choose response transformations for multiple linear regression or experimental design models.

This text is for graduates and undergraduates with a strong mathematical background. The prerequisites for this text are linear algebra and a calculus based course in statistics.

About the authors

David Olive is a Professor at Southern Illinois University, Carbondale, IL, USA.  His research interests include the development of computationally practical robust multivariate location and dispersion estimators, robust multiple linear regression estimators, and resistant dimension reduction estimators.

Table of contents (14 chapters)

Buy this book

eBook $69.99
price for USA (gross)
  • ISBN 978-3-319-55252-1
  • Digitally watermarked, DRM-free
  • Included format: EPUB, PDF
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Hardcover $89.99
price for USA
  • Customers within the U.S. and Canada please contact Customer Service at 1-800-777-4643, Latin America please contact us at +1-212-460-1500 (Weekdays 8:30am – 5:30pm ET) to place your order.
  • Due: May 17, 2017
  • ISBN 978-3-319-55250-7
  • Free shipping for individuals worldwide
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Bibliographic Information

Bibliographic Information
Book Title
Linear Regression
Authors
Copyright
2017
Publisher
Springer International Publishing
Copyright Holder
Springer International Publishing AG
eBook ISBN
978-3-319-55252-1
DOI
10.1007/978-3-319-55252-1
Hardcover ISBN
978-3-319-55250-7
Edition Number
1
Number of Pages
XIV, 494
Number of Illustrations and Tables
57 b/w illustrations
Topics