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MON
Monahan, John F
Primer on linear models
Chapman & Hall
2008
Boca Raton :
xiv, 287 p. ;
ill.,
23 cm
1995.00
INR
01
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
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 estimator
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DAIICT
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1995.00
519.5 MON
033766
2023-04-19
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