Bapat has created an extremely useful reference on/guide to estimation methods and linear models. The first chapter is a very concise linear algebra review which is really nice (who can remember all that stuff?). The scope is wide enough to get singular decomposition, principal components, and rank additivity. Very useful for beginning statisticians and researchers like myself. My only complaint is that the proofs are often cursory and rather terse, leaving out many "obvious" steps, and sometimes complex assertions are made with no proof whatsoever. However, many other texts provide these proofs such as Arnold's "Theory of Linear Models and Multivariate Analysis."

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