The linear model and hypothesis : a general unifying theory /

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Bibliographic Details
Author / Creator:	Seber, G. A. F. (George Arthur Frederick), 1938- author.
Imprint:	Cham : Springer, [2015] ©2015
Description:	1 online resource.
Language:	English
Series:	Springer series in statistics Springer series in statistics.
Subject:	Linear models (Statistics) Statistical hypothesis testing. Mathematical statistics. Linear models (Statistics) Mathematical statistics. Statistical hypothesis testing.
Format:	E-Resource Book
URL for this record:	http://pi.lib.uchicago.edu/1001/cat/bib/11096479

Hidden Bibliographic Details
ISBN:	9783319219301 3319219308 9783319219295 3319219294 9783319219295
Notes:	Includes bibliographical references and index. Online resource; title from PDF title page (EBSCO, viewed October 14, 2015).
Summary:	This book provides a concise and integrated overview of hypothesis testing in four important subject areas, namely linear and nonlinear models, multivariate analysis, and large sample theory. The approach used is a geometrical one based on the concept of projections and their associated idempotent matrices, thus largely avoiding the need to involve matrix ranks. It is shown that all the hypotheses encountered are either linear or asymptotically linear, and that all the underlying models used are either exactly or asymptotically linear normal models. This equivalence can be used, for example, to extend the concept of orthogonality in the analysis of variance to other models, and to show that the asymptotic equivalence of the likelihood ratio, Wald, and Score (Lagrange Multiplier) hypothesis tests generally applies.
Other form:	Printed edition: 9783319219295
Standard no.:	10.1007/978-3-319-21930-1

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