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# Linear Models in Statistics. 2nd Edition

• Published: February 2008
• Region: Global
• 688 Pages
• John Wiley and Sons Ltd

The essential introduction to the theory and application of linear models—now in a valuable new edition

Since most advanced statistical tools are generalizations of the linear model, it is neces-sary to first master the linear model in order to move forward to more advanced concepts. The linear model remains the main tool of the applied statistician and is central to the training of any statistician regardless of whether the focus is applied or theoretical. This completely revised and updated new edition successfully develops the basic theory of linear models for regression, analysis of variance, analysis of covariance, and linear mixed models. Recent advances in the methodology related to linear mixed models, generalized linear models, and the Bayesian linear model are also addressed.

Linear Models in Statistics, Second Edition includes full coverage of advanced topics, such as mixed and generalized linear models, Bayesian linear models, two-way models with empty cells, geometry of least squares, vector-matrix calculus, simultaneous inference, and logistic and nonlinear regression. Algebraic, geometrical, frequentist, and Bayesian approaches to both the inference

Preface.

1. Introduction.

2. Matrix Algebra.

3. Random Vectors and Matrices.

4. Multivariate Normal Distribution.

5. Distribution of Quadratic Forms in y.

6. Simple Linear Regression.

7. Multiple Regression: Estimation.

8. Multiple Regression: tests of Hypotheses and Confidence Intervals.

9. Multiple Regression: Model Validation and Diagnostics.

10. Multiple Regression: random x's.

11. Multiple Regression: Bayesian Inference.

12. Analysis-of-Variance Models.

13. One-Way Analysis-of-Variance: balanced Case.

14. Two-Way Analysis-of Variance: Balanced Case.

15. Analysis-of-Variance: The Cell Means Model for Unbalanced Data.

16. Analysis-of-Covariance.

17. Linear Mixed Models.

Appendix A. Answers and Hits to the Problems.

References.

Index.

"This indeed clearly written book will do great service for advanced undergraduate and also for PhD students." (International Statistical Review, December 2008)

"This indeed clearly written book will do great service for advanced undergraduate and also for PhD students." (International Statistical Review, Dec 2008)

"This well-written book represents various topics on linear models with great clarity in an easy-to-understand style." (CHOICE, Aug 2008)

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