ISBN-10:
3642093531
ISBN-13:
9783642093531
Pub. Date:
11/19/2010
Publisher:
Springer Berlin Heidelberg
Linear Models and Generalizations: Least Squares and Alternatives / Edition 3

Linear Models and Generalizations: Least Squares and Alternatives / Edition 3

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Overview

Linear Models and Generalizations: Least Squares and Alternatives / Edition 3

Revised and updated with the latest results, this Third Edition explores the theory and applications of linear models. The authors present a unified theory of inference from linear models and its generalizations with minimal assumptions. They not only use least squares theory, but also alternative methods of estimation and testing based on convex loss functions and general estimating equations. Highlights of coverage include sensitivity analysis and model selection, an analysis of incomplete data, an analysis of categorical data based on a unified presentation of generalized linear models, and an extensive appendix on matrix theory.

Product Details

ISBN-13: 9783642093531
Publisher: Springer Berlin Heidelberg
Publication date: 11/19/2010
Series: Springer Series in Statistics
Edition description: Softcover reprint of hardcover 3rd ed. 2008
Pages: 572
Product dimensions: 6.10(w) x 9.25(h) x 0.05(d)

Table of Contents

The Simple Linear Regression Model.- The Multiple Linear Regression Model and Its Extensions.- The Generalized Linear Regression Model.- Exact and Stochastic Linear Restrictions.- Prediction in the Generalized Regression Model.- Sensitivity Analysis.- Analysis of Incomplete Data Sets.- Robust Regression.- Models for Categorical Response Variables.

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