Linear Model Theory

Dale L. Zimmerman ()
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Dale L. Zimmerman: University of Iowa, Department of Statistics and Actuarial Science

in Springer Books from Springer

Date: 2020
ISBN: 978-3-030-52063-2
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Chapters in this book:

Ch 1 A Brief Introduction

Dale L. Zimmerman

Ch 2 Selected Matrix Algebra Topics and Results

Dale L. Zimmerman

Ch 3 Generalized Inverses and Solutions to Systems of Linear Equations

Dale L. Zimmerman

Ch 4 Moments of a Random Vector and of Linear and Quadratic Forms in a Random Vector

Dale L. Zimmerman

Ch 5 Types of Linear Models

Dale L. Zimmerman

Ch 6 Estimability

Dale L. Zimmerman

Ch 7 Least Squares Estimation for the Gauss–Markov Model

Dale L. Zimmerman

Ch 8 Least Squares Geometry and the Overall ANOVA

Dale L. Zimmerman

Ch 9 Least Squares Estimation and ANOVA for Partitioned Models

Dale L. Zimmerman

Ch 10 Constrained Least Squares Estimation and ANOVA

Dale L. Zimmerman

Ch 11 Best Linear Unbiased Estimation for the Aitken Model

Dale L. Zimmerman

Ch 12 Model Misspecification

Dale L. Zimmerman

Ch 13 Best Linear Unbiased Prediction

Dale L. Zimmerman

Ch 14 Distribution Theory

Dale L. Zimmerman

Ch 15 Inference for Estimable and Predictable Functions

Dale L. Zimmerman

Ch 16 Inference for Variance–Covariance Parameters

Dale L. Zimmerman

Ch 17 Empirical BLUE and BLUP

Dale L. Zimmerman

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DOI: 10.1007/978-3-030-52063-2

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