http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
with applications in engineering and the sciences
1 online resource (xiii, 496 pages) : illustrations
"Generalized Linear Models: With Applications in Engineering and the Sciences, Second Edition continues to provide a clear introduction to the theoretical foundations and key applications of generalized linear models (GLMs). Maintaining the same nontechnical approach as its predecessor, this update has been thoroughly extended to include the latest developments, relevant computational approaches, and modern examples from the fields of engineering and physical sciences." "The authors demonstrate the diverse applications of GLMs through numerous examples, from classical applications in the fields of biology andbiopharmaceuticals to more modern examples related to engineering and quality assurance. The Second Edition has been designed to demonstrate the growing computational nature of GLMs, as SAS, Minitab, JMp, and R software packages are used throughout the book to demonstrate fitting and analysis of generalized linear models, perform inference, and conduct diagnostic checking. Numerous figures and screen shots illustrating computer output are provided, and a related FTP site houses supplementary material, including computer commands and additional data sets." "Generalized Linear Models, Second Edition is an excellent book for courses on regression analysis and regression modeling at the upper-undergraduate and graduate level. It also servesas a valuable reference for engineers, scientists, and statisticians who must understand and apply GLMs in their work."--Jacket.
Front Matter -- Introduction to Generalized Linear Models -- Linear Regression Models -- Nonlinear Regression Models -- Logistic and Poisson Regression Models -- The Generalized Linear Model -- Generalized Estimating Equations -- Random Effects in Generalized Linear Models -- Designed Experiments and the Generalized Linear Model -- Appendix A.1: Background on Basic Test Statistics -- Appendix A.2: Background from the Theory of Linear Models -- Appendix A.3: The Gauss₆Markov Theorem, Var(e) = sI -- Appendix A.4: The Relationship Between Maximum Likelihood Estimation of the Logistic Regression Model and Weighted Least Squares -- Appendix A.5: Computational Details for GLMs for a Canonical Link -- Appendix A.6: Computational Details for GLMs for a Noncanonical Link -- References -- Index -- Wiley Series in Probability and Statistics --
Revised edition of: Generalized linear models / Raymond H. Myers, Douglas C. Montgomery, G. Geoffrey Vining. c2002.
Includes bibliographical references and index.
Wiley series in probability and statistics