Generalized Linear Models: With Applications in Engineering and the Sciences / Edition 1 available in Hardcover
- Pub. Date:
Includes thorough treatment of logistic and Poisson regression.
• Introduction to generalized estimating questions.
• Numerous examples in fields ranging from biology and biopharmaceuticals to engineering and quality assurance.
• Provides guidance in using widely available software to illustrate all aspects of model-fitting, inference, and diagnostic testing.
About the Author
RAYMOND H. MYERS is Professor Emeritus in the Department of Statistics at Virginia Tech in Blacksburg, Virginia.
DOUGLAS C. MONTGOMERY is Professor in the Department of Industrial Engineering at Arizona State University in Tempe, Arizona.
G. GEOFFREY VINING is Professor and Head of the Department of Statistics at Virginia Tech in Blacksburg, Virginia.
Table of Contents
1. Introduction to Generalized Linear Models.
2. Linear Regression Models.
3. Nonlinear Regression Models.
4. Logistic and Poisson Regression Models.
5. The Family of Generalized Linear Models.
6. Generalized Estimating Equations.
7. Further Advances and Applications in GLM.
Appendix 1: Background on Basic Test Statistics.
Appendix 2: Background from the Theory of Linear Models.
Appendix 3: The Gauss-Markov Theroem.
Appendix 4: The Relationship Between Maximum Likelihood Estimation of the Logistic Regression Model and Weighted Least Squares.
Appendix 5: Computational Details for GLMs for a Canonical Link.
Appendix 6: Computational Details for GLMs for a Noncanonical Link.