Linear Models and the Relevant Distributions and Matrix Algebra

"The book presents procedures for making statistical inferences on the basis of the classical linear statistical model, and discusses the various properties of those procedures. Supporting material on matrix algebra and statistical distributions is interspersed with a discussion of relevant inferential procedures and their properties. The coverage ranges from MS-level to advanced researcher. In particular, the material in chapters 6-7 is not covered in an approachable manner in any other books, and greatly generalizes the traditional normal-based linear regression model to the elliptical distributions, thus greatly elucidating the advanced reader on just how far this class of models can be extended. Refreshingly, the material also goes beyond the classical 20th century coverage to include some 21st century topics like microarray (big) data analysis, and control of false discovery rates in large scale experiments...From the point of view of an advanced instructor and researcher on the subject, I very strongly recommend publication...Note that...this book provides the coverage of 3 books, hence the title purporting to provide a 'unified approach' (of 3 related subjects) is indeed accurate."
~Alex Trindade, Texas Tech University

"The book is very well written, with exceptional attention to details. It provides detailed derivations or proofs of almost all the results, and offers in-depth coverage of the topics discussed. Some of these materials (e.g., spherical/elliptical distributions) are hard to find from other sources. Anyone who is interested in linear models should benefit from reading this book and find it especially useful for a thorough understanding of the linear-model theory in a unified framework... The book is a delight to read."
~Huaiqing Wu, Iowa State University

"This book is useful in two ways: an excellent text book for a graduate level linear models course, and for those who want to learn linear models from a theoretical perspective...I genuinely enjoyed reading Ch 1and Ch 4 (Introduction and General Linear Models). Often, the hardest part of teaching linear models from a theoretical perspective is to motivate the students about the utility and generality of such models and the related theory. This book does an excellent job in this area, while presenting a solid theoretical foundation."
~Arnab Maity, North Carolina State University