Linear Models and the Relevant Distributions and Matrix Algebra

David A. Harville served for 10 years as a mathematical statistician in the Applied Mathematics Research Laboratory of the Aerospace Research Laboratories (at Wright-Patterson AFB, Ohio), for 20 years as a full professor in Iowa State University's Department of Statistics (where he now has emeritus status), and 7 years as a research staff member of the Mathematical Sciences Department of IBM's T.J. Watson Research Center. He has extensive experience in the area of linear statistical models, having taught (on numerous occasions) M.S. and Ph.D. level courses on that subject, having been the thesis advisor of 10 Ph.D. graduates, and having authored (or co-authored) 3 books and more than 80 research articles. His work has been recognized through his election as a Fellow of the American Statistical Association and of the Institute of Mathematical Statistics and as a member of the International Statistical Institute.

Linear Models and the Relevant Distributions and Matrix Algebra: A Unified Approach, Volume 2 covers several important topics that were not included in the first volume. The second volume complements the first, providing detailed solutions to the exercises in both volumes.

Part 1: Additional Topics 8. Constrained Linear Models and Related Topics Part 2: Exercises and Solutions 2. Matrix Algebra: A Primer 3. Random Vectors and Matrices 4. The General Linear Model 5. Estimation and Prediction: Classical Approach 6. Some Relevant Distributions and Their Properties 7. Confidence Intervals (or Sets) and Tests of Hypotheses 8. Constrained Linear Models and Related Topics