Description 
xv, 427 pages : illustrations ; 25 cm 
Series 
Springer series in statistics 

Springer series in statistics.

Contents 
1. Introduction  2. Linear Models  3. The 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  A. Matrix Algebra  C. Software for Linear Regression Models 
Summary 
"This book provides an uptodate account of the theory and applications of linear models. It can be used as a text for courses in statistics at the graduate level as well as an accompanying text for other courses in which linear models play a part. The authors present a unified theory of inference from linear models 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."BOOK JACKET 
Notes 
Previous ed.: New York : Springer, 1995 
Bibliography 
Includes bibliographical references (pages [403]419) and index 
Subject 
Linear models (Statistics)

Author 
Toutenburg, Helge.

LC no. 
99014735 
ISBN 
0387988483 : 
