Linear regression

Series: Lecture Notes in Statistics , Vol. 175

Jurgen Gross

406 pages, parution le 13/11/2003

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Résumé

The book covers the basic theory of linear regression models and presents a comprehensive survey of different estimation techniques as alternatives and complements to least squares estimation. The relationship between different estimators is clearly described and categories of estimators are worked out in detail. Proofs are given for the most relevant results, and the presented methods are illustrated with the help of numerical examples and graphics. Special emphasis is laid on the practicability, and possible applications are discussed. The book is rounded off by an introduction to the basics of decision theory and an appendix on matrix algebra.

Point estimation and linear regression
- Fundamentals
- The Linear Regression Model
Alternatives to Least Squares Estimation
- Alternative Estimators
- Linear Admissibility
Miscellaneous Topics
- The Covariance Matrix of the Error Vector
- Regression Diagnostics
A- Matrix Algebra
B- Stoachstic Vectors
C- An Example Analysis with R
References
Index

Caractéristiques techniques

	PAPIER
Éditeur(s)	Springer
Auteur(s)	Jurgen Gross
Parution	13/11/2003
Nb. de pages	406
Format	15,5 x 23,5
Couverture	Broché
Poids	620g
Intérieur	Noir et Blanc
EAN13	9783540401780