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Linear Models and Generalizations

  • Kartonierter Einband
  • 592 Seiten
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Third Edition explores the theory and applications of linear models. It presents a unified theory of inference from linear models ... Weiterlesen
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Beschreibung

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.

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.

Autorentext
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.

Zusammenfassung
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)

Inhalt

1. Introduction.- 2. The Simple Linear Regression Model.- 3. The Multiple 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.- Fitting Smooth Functions.- Appendix A: Matrix Algebra.

Produktinformationen

Titel: Linear Models and Generalizations
Untertitel: Least Squares and Alternatives
Autor:
EAN: 9783642093531
ISBN: 3642093531
Format: Kartonierter Einband
Genre: Mathematik
Anzahl Seiten: 592
Gewicht: 883g
Größe: H235mm x B155mm x T31mm
Jahr: 2010
Auflage: Softcover reprint of hardcover 3rd ed. 2008.

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