Linear Models and Generalizations : Least Squares and Alternatives

C. Radhakrishna Rao

ISBN 10: 3540742263 / ISBN 13: 9783540742265

Edité par Springer Berlin Heidelberg, 2007

A propos de cet article

Druck auf Anfrage Neuware - Printed after ordering - Thebookisbasedonseveralyearsofexperienceofbothauthorsinteaching linear models at various levels. It gives an up-to-date account of the theory and applications of linear models. The book can be used as a text for courses in statistics at the graduate level and as an accompanying text for courses in other areas. Some of the highlights in this book are as follows. A relatively extensive chapter on matrix theory (Appendix A) provides the necessary tools for proving theorems discussed in the text and o ers a selectionofclassicalandmodernalgebraicresultsthatareusefulinresearch work in econometrics, engineering, and optimization theory. The matrix theory of the last ten years has produced a series of fundamental results aboutthe de niteness ofmatrices,especially forthe di erences ofmatrices, which enable superiority comparisons of two biased estimates to be made for the rst time. We have attempted to provide a uni ed theory of inference from linear models with minimal assumptions. Besides the usual least-squares theory, alternative methods of estimation and testing based on convex loss fu- tions and general estimating equations are discussed. Special emphasis is given to sensitivity analysis and model selection. A special chapter is devoted to the analysis of categorical data based on logit, loglinear, and logistic regression models. The material covered, theoretical discussion, and a variety of practical applications will be useful not only to students but also to researchers and consultants in statistics.

N° de réf. du vendeur 9783540742265

Détails bibliographiques

• Titre: Linear Models and Generalizations : Least Squares and Alternatives
• Éditeur: Springer Berlin Heidelberg
• Date de parution: 2007
• Langue: anglais
• ISBN à 10 chiffres: 3540742263
• ISBN à 13 chiffres: 9783540742265
• Reliure: Buch
• Édition: 3ème Édition
• État de l'article: Neu
• Dimensions: 241 L x 160 H x 37 P (en millimètres) 241 millimètres de largeur par 160 millimètres de hauteur par 37 millimètres de profondeur
• Poids: 1051 grammes

A propos de ce titre

Synopsis

Thoroughly revised and updated with the latest results, this Third Edition provides an 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. 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 include sensitivity analysis and model selection, an analysis of incomplete data, and an analysis of categorical data based on a unified presentation of generalized linear models. There is also an extensive appendix on matrix theory that is particularly useful for researchers in econometrics, engineering, and optimization theory. This text is recommended for courses in statistics at the graduate level as well as for other courses in which linear models play a role.

Présentation de l'éditeur

Third Edition explores the theory and applications of linear models. It presents a unified theory of inference from linear models and its generalizations with minimal assumptions, using least squares theory and alternative methods of estimation and testing.