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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.
This book contains 296 exercises and solutions covering a wide variety of topics in linear model theory, including generalized inverses, estimability, best linear unbiased estimation and prediction, ANOVA, confidence intervals, simultaneous confidence intervals, hypothesis testing, and variance component estimation.
Offers a systematic way to learn about antedependence models and the important statistical inference procedures associated with these models. This title presents both informal methods of inference, such as graphical methods, and formal likelihood-based methods.
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