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A Primer on Linear Models


By: John F Monahan

Chapman & Hall (CRC Press)

Paperback | Apr 2008 | #171414 | ISBN-13: 9781420062014
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About this book

Since the linear model forms the groundwork for most applied statistics, a course on the theory of the linear model is often required in most graduate statistics programs. A Primer on Linear Models presents a concise yet complete foundation for understanding basic linear models. Designed for a one-semester graduate course, this textbook begins with a practical discussion of basic algebra and geometry concepts as they apply to the linear model. The book then proceeds to an in-depth treatment of more advanced topics such as the Gauss-Markov model. The text also includes exercises of various levels of difficulty and features the constant use of non full-rank design matrices.


Preface. Examples of the General Linear Model. The Linear Least Squares Problem. Estimability and Least Squares Estimators. Gauss--Markov Model. Distributional Theory. Statistical Inference. Further Topics in Testing. Variance Components and Mixed Models. The Multivariate Linear Model. Appendices. Bibliography.

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