You are here

Linear Model Theory: Univariate, Multivariate, and Mixed Models

Keith E. Muller and Paul W. Stewart
John Wiley
Publication Date: 
Number of Pages: 
Wiley Series in Probability and Statistics
[Reviewed by
Ita Cirovic Donev
, on

Linear Model Theory presents us with a unified treatment of univariate, multivariate and mixed models. This book is definitely not for a novice or even a beginner in statistics. It is written in a terse mathematical style with no official invitiation to the subject. Most of the proofs are left as an exercise to the reader. There is not much of a discussion between the presentation of theorems, corollaries, etc.

Exercises are provided at the end of each chapter. The majority of the exercises are theoretical problems where only some are of computational nature. The computational exercises can be completed with major statistical software such as S+, SAS, etc.

I see this text as a reference guide to the models under the title and as such it is an excellent book for graduate students in statistics and professional researchers. As a reference it will provide one with a quick guide to the theretical world of the univariate, multivariate and mixed models. Also one can further broaden its horizons with vast additional references the authors provides within the text.

Ita Cirovic Donev is a PhD candidate at the University of Zagreb. She hold a Masters degree in statistics from Rice University. Her main research areas are in mathematical finance; more precisely, statistical mehods of credit and market risk. Apart from the academic work she does consulting work for financial institutions.

The table of contents is not available.