Linear models and generalizations
least squares and alternatives
Rao, C. Radhakrishna.
text
bibliography
nyu
New York
Springer
2008
3rd extended ed.
monographic
eng
xix, 570 p. : ill. ; 25 cm.
"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...
TOC 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
general
C. Radhakrishna Rao ... [et al.]
Print version:
Linear models and generalizations.
Berlin ; New York : Springer, ©2008
(OCoLC)173807301.
Includes Bibliographical References and Index.
AS
Mathematical satistics
Linear models (Statistics)
519.5 LIN 2008
Springer series in statistics
9783540742265
9780387988481
http://lib.ewubd.edu/ebook/4327
http://lib.ewubd.edu/ebook/4327
BD-DhEWU
110604
20171207133255.0
4327
eng