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Primer on linear models

By: Monahan, John F.
Series: Texts in statistical science.Publisher: Boca Raton : Chapman & Hall 2008Description: xiv, 287 p. ; ill., 23 cm.ISBN: 9780367241889.Subject(s): Linear models | Aggregation, Gauss-Markov model | ANOVA | Best linear unbiased estimator | Cell means model | Cochran's theorem | Distributional theory | Eigenvalues | Estimability | First-order autoregressive error models | Graam-Schmid orthonormalization | Hypothesis testing | Pythagorean theorem | Multivariate linear model | Nested model, two way | Orthogonal polynomials | Regression models | Two-sample problem | Unbiased estimators | Zero estimatorDDC classification: 519.5 Summary: A Primer on Linear Models presents a unified, thorough, and rigorous development of the theory behind the statistical methodology of regression and analysis of variance (ANOVA). It seamlessly incorporates these concepts using non-full-rank design matrices and emphasizes the exact, finite sample theory supporting common statistical methods. This text enables complete comprehension of the material by taking a general, unifying approach to the theory, fundamentals, and exact results of linear models.
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Includes bibliographical references and index.

A Primer on Linear Models presents a unified, thorough, and rigorous development of the theory behind the statistical methodology of regression and analysis of variance (ANOVA). It seamlessly incorporates these concepts using non-full-rank design matrices and emphasizes the exact, finite sample theory supporting common statistical methods. This text enables complete comprehension of the material by taking a general, unifying approach to the theory, fundamentals, and exact results of linear models.

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