ISBN: 9783540742265 - Linear Models and Generalizations: Least Squares and Alternatives (springer Series in Statistics) (11 results)

Condition: New. Brand New! Fast Delivery This is an International Edition and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 6-10 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.…

Hardcover. Condition: Sehr gut. Third extended Edition. 591 pp. Very well preserved copy with only slight signs of wear 324 Sprache: Englisch Gewicht in Gramm: 1213.

Condition: New. pp. xx + 570 3rd Extended Edition.

Condition: New. pp. xx + 570 Illus.

Buch. 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.…

Hardcover. Condition: Like New. LIKE NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

Condition: gut. 2007. Linear Models and Generalizations: Least Squares and Alternatives (Springer Series in Statistics) In deutscher Sprache. pages.

Buch. 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. 596 pp. Englisch.…

Gebunden. 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 .…

Buch. 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 KG, Sachsenplatz 4-6, 1201 Wien 596 pp. Englisch.…

Condition: New. PRINT ON DEMAND pp. xx + 570.