Linear Models and Generalizations: Least Squares and Alternatives (Springer Series in Statistics)
Rao, C. Radhakrishna; Toutenburg, Helge; Shalabh; Heumann, Christian
ISBN 10: 3642093531 ISBN 13: 9783642093531
Published by Springer, 2010
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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.
Review:
From the reviews of the third edition:
"The book contains a massive amount of useful results related to the world of linear models. ... I find my life more comfortable when I have this book in my bookshelf while checking whether some results have appeared in the literature. ... a natural source book for a student and researcher of linear models. ... written with great care and, of course, with great skills under the leadership of Professor C. Radhakrishna Rao. This is a very useful book and the authors earn congratulations." (Simo Puntanen, International Statistical Review, Vol. 75 (3), 2007)
"The book gives an up-to-date and comprehensive account of the theory and applications of linear models along with a number of new results. Throughout its ten chapters as well as its appendices, it covers theoretical issues and practical applications that make it suitable and useful not only to students but also to researchers and consultants in statistics." (Vangelis Grigoroudis, Zentralblatt MATH, Vol. 1151, 2009)
"This book has two laudable strengths. First, the coverage of topics is vast and varied. Second, extensive material is included on many modern, cutting-edge directions. ... The book would also function as an excellent reference for graduate students and researchers on classical and current developments in linear model theory." (Joseph Cavanaugh, Journal of the American Statistical Association, Vol. 104 (486), June, 2009)
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Title: Linear Models and Generalizations: Least ...
Publisher: Springer
Publication Date: 2010
Binding: Soft cover
Condition: New
Edition: 3rd Edition
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Linear Models and Generalizations: Least Squares and Alternatives (Springer Series in Statistics), 3rd edition
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Soft cover. Condition: New. Dust Jacket Condition: New. 3rd Edition. **INTERNATIONAL EDITION** Read carefully before purchase: This book is the international edition in mint condition with the different ISBN and book cover design, the major content is printed in full English as same as the original North American edition. The book printed in black and white, generally send in twenty-four hours after the order confirmed. All shipments go through via USPS/UPS/DHL with tracking numbers. Great professional textbook selling experience and expedite shipping service. Seller Inventory # ABE-16582425458
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Linear Models and Generalizations
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Essential text for graduate statistics courses and courses where linear models play a part Presents advanced research results and gives an overview of generalizations New edition has been extensivley revised and contains the latest results . Seller Inventory # 5048368
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Taschenbuch. Condition: Neu. Linear Models and Generalizations | Least Squares and Alternatives | C. Radhakrishna Rao (u. a.) | Taschenbuch | xix | Englisch | 2010 | Springer Vieweg | EAN 9783642093531 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Seller Inventory # 107211834
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Linear Models and Generalizations : Least Squares and Alternatives
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Taschenbuch. Condition: Neu. 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. Seller Inventory # 9783642093531
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Linear Models and Generalizations
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 592 pp. Englisch. Seller Inventory # 9783642093531
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Linear Models and Generalizations
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Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 592 pp. Englisch. Seller Inventory # 9783642093531
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Linear Models and Generalizations
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