Unified rigorous framework for best linear unbiased estimation and prediction enhances theoretical understanding
Concrete examples and special cases illustrate major concepts, making the material accessible
Comprehensive exercises support both students and instructors in mastering the subject
Generalized inverses allow for flexible modeling with non-full rank matrices
Emphasis on estimability, partitioned ANOVA, and prediction addresses advanced topics not commonly found in other textbooks
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Linear Model Theory: With Examples and Exercises Zimmerman, Dale L.
This textbook presents a unified and rigorous approach to best linear unbiased estimation and prediction of parameters and random quantities in linear models, as well as other theory upon which much of the statistical methodology associated with linear models is based. Th