Textbook in PDF format

This book contains 296 exercises and solutions covering a wide variety of topics in linear model theory, including generalized inverses, estimability, best linear unbiased estimation and prediction, ANOVA, confidence intervals, simultaneous confidence intervals, hypothesis testing, and variance component estimation. The models covered include the Gauss-Markov and Aitken models, mixed and random effects models, and the general mixed linear model. Given its content, the book will be useful for students and instructors alike. Readers can also consult the companion textbook Linear Model Theory - With Examples and Exercises by the same author for the theory behind the exercises.
A Brief Introduction
Selected Matrix Algebra Topics and Results
Generalized Inverses and Solutions to Systems of Linear Equations
Moments of a Random Vector and of Linear and Quadratic Forms in a Random Vector
Types of Linear Models
Least Squares Estimation for the Gauss–Markov Model
Least Squares Geometry and the Overall ANOVA
Least Squares Estimation and ANOVA for Partitioned Models
Constrained Least Squares Estimation and ANOVA
Best Linear Unbiased Estimation for the Aitken Model
Model Misspecification
Best Linear Unbiased Prediction
Distribution Theory
Inference for Estimable and Predictable Functions
Inference for Variance–Covariance Parameters
Empirical BLUE and BLUP