Handbook of Regression Methods
eBook - ePub

Handbook of Regression Methods

  1. 638 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Handbook of Regression Methods

About this book

Handbook of Regression Methods concisely covers numerous traditional, contemporary, and nonstandard regression methods. The handbook provides a broad overview of regression models, diagnostic procedures, and inference procedures, with emphasis on how these methods are applied. The organization of the handbook benefits both practitioners and researchers, who seek either to obtain a quick understanding of regression methods for specialized problems or to expand their own breadth of knowledge of regression topics.

This handbook covers classic material about simple linear regression and multiple linear regression, including assumptions, effective visualizations, and inference procedures. It presents an overview of advanced diagnostic tests, remedial strategies, and model selection procedures. Finally, many chapters are devoted to a diverse range of topics, including censored regression, nonlinear regression, generalized linear models, and semiparametric regression.

Features



  • Presents a concise overview of a wide range of regression topics not usually covered in a single text


  • Includes over 80 examples using nearly 70 real datasets, with results obtained using R


  • Offers a Shiny app containing all examples, thus allowing access to the source code and the ability to interact with the analyses

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Yes, you can access Handbook of Regression Methods by Derek Scott Young in PDF and/or ePUB format, as well as other popular books in Mathematics & Probability & Statistics. We have over one million books available in our catalogue for you to explore.

Information

Publisher
CRC Press
Year
2018
Print ISBN
9781498775298
eBook ISBN
9781351650748

Table of contents

  1. Cover
  2. Half Title
  3. Title Page
  4. Copyright Page
  5. Dedication
  6. Table of Contents
  7. List of Examples
  8. Preface
  9. I Simple Linear Regression
  10. II Multiple Linear Regression
  11. III Advanced Regression Diagnostic Methods
  12. IV Advanced Regression Models
  13. V Appendices
  14. Bibliography
  15. Index