This book has the following special features:
Use of simple statistical ideas such as linear zero functions and covariance adjustment to explain the fundamental as well as advanced concepts  
Emphasis on statistical interpretation of complex algebraic results  
A thorough treatment of the singular linear model, including the case of multivariate response  
A unified discussion of models with a partially unknown dispersion matrix, including mixedeffects / variance components models and models for spatial and time series data  
Insight into updates in the linear model and their connection with diagnostics, design, variable selection, the Kalman filter, etc.  
An extensive discussion of the foundations of linear inference, along with linear alternatives to least squares  
Coverage of other special topics such as collinearity, stochastic and inequality constraints, misspecified models, etc.  
Simpler proofs of numerous known results  
Pointers to current research through examples and exercises 
Contents:
644pp  Pub. date: Mar 2003 
ISBN 9810245920  US$82 / £60 
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