Statistical Inference in Linear Models (v. 1) (Probability & Mathematical Statistics S.)

This is a comprehensive account of the theory of the linear model, and covers a wide range of statistical methods. Topics covered include estimation, testing, confidence regions, Bayesian methods and optimal design. These are all supported by practical examples and results; a concise description of these results is included in the appendices. Material relating to linear models is discussed in the main text, but results from related fields such as linear algebra, analysis, and probability theory are included in the appendices. The information includes advances in the UK and US, as well as the USSR and German Democratic Republic.