Linear models and generalizations [electronic resource] : least squares and alternatives / C. Radhakrishna Rao ... [et al.] ; with contributions by Michael Schomaker.

Contributor(s):

Material type: Text

TextSeries: Springer series in statisticsPublication details: Berlin ; New York : Springer, c2008.Edition: 3rd extended edDescription: 1 online resource (xix, 570 p.) : illISBN:

9783540742272
3540742271
9783540742265
3540742263
6611355308
9786611355302

Subject(s):

Linear models (Statistics)

Additional physical formats: Print version:: Linear models and generalizations.Review: "This book provides an up-to-date 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, not only through least squares theory, but also using alternative methods of estimation and testing based on convex loss functions and general estimating equations. It can be used as a text for courses in statistics at the graduate level as well as an accompanying text for other courses in which linear models play a part." "For this third edition the text has been extensively revised and contains the latest developments in the area of linear models. Many new topics like regression techniques, nonparametric regression, bagging, boosting, regression trees and full likelihood methods for correlated response in categorical data have been included."--Jacket.

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Holdings
Item type	Current library	Call number	Copy number	Status	Date due	Barcode
General Books	CUTN Central Library Sciences	519.5 (Browse shelf(Opens below))	1	Available		10708

Includes bibliographical references (p. [539]-562) and index.

Online version restricted to NUS staff and students only through NUSNET.

"This book provides an up-to-date 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, not only through least squares theory, but also using alternative methods of estimation and testing based on convex loss functions and general estimating equations. It can be used as a text for courses in statistics at the graduate level as well as an accompanying text for other courses in which linear models play a part." "For this third edition the text has been extensively revised and contains the latest developments in the area of linear models. Many new topics like regression techniques, nonparametric regression, bagging, boosting, regression trees and full likelihood methods for correlated response in categorical data have been included."--Jacket.

Mode of access: World Wide Web.

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