Monahan, John F

Primer on linear models - Boca Raton : Chapman & Hall 2008 - xiv, 287 p. ; ill., 23 cm - Texts in statistical science .

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.


Linear models
Aggregation, Gauss-Markov model
Best linear unbiased estimator
Cell means model
Cochran's theorem
Distributional theory
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 estimator

519.5 / MON

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