Revised and updated with the latest results, this Third Edition explores the
theory and applications of linear models. The authors present a unified theory
of inference from linear models and its generalizations with minimal
assumptions. They not only use least squares theory, but also alternative
methods of estimation and testing based on convex loss functions and general
estimating equations. Highlights of coverage include sensitivity analysis and
model selection, an analysis of incomplete data, an analysis of categorical data
based on a unified presentation of generalized linear models, and an extensive
appendix on matrix theory.