Linear models and generalizations : least squares and alternatives / C. Radhakrishna Rao ... [et al.] - 3rd extended ed. - New York : Springer, 2008. - xix, 570 p. : ill. ; 25 cm. - Springer series in statistics. .

Print version:
Linear models and generalizations.
Berlin ; New York : Springer, ©2008
(OCoLC)173807301.

Includes Bibliographical References and Index.

1. Introduction --
2. The Simple Linear Regression Model --
3. The Multiple Linear Regression Model --
4. The Generalized Linear Regression Model --
5. Exact and Stochastic Linear Restrictions --
6. Prediction Problems in the Generalized Regression Model --
7. Sensitivity Analysis --
8. Analysis of Incomplete Data Sets --
9. Robust Regression --
10. Models for Categorical Response Variables --
Fitting Smooth Functions --
Appendix A: Matrix Algebra Table of contents

"This book provides an up-to-date account of the theory and applications of linear models. The authors present a unified theory of inference from linear models and its generalizations with minimal assumptions, not only through least squares theory, but also using alternative methods of estimation and testing based on convex loss functions and general estimating equations. It can be used as a text for courses in Read more...



9783540742265 9780387988481

Mathematical satistics Linear models (Statistics)

519.5 / LIN 2008

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