Springer series in statistics the linear model and hypothesis
Uiterlijk 30 oktober in huis
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.
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.
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Taal: en
Bindwijze: Paperback
Oorspronkelijke releasedatum: 23 augustus 2016
Aantal pagina's: 205
Illustraties: Nee
Hoofdauteur: George Seber
Tweede Auteur: George A. F. Seber
Co Auteur: Seber George
Hoofduitgeverij: Springer International Publishing Ag
Editie: 1
Extra groot lettertype: Nee
Product breedte: 155 mm
Product lengte: 235 mm
Studieboek: Ja
Verpakking breedte: 155 mm
Verpakking hoogte: 18 mm
Verpakking lengte: 235 mm
Verpakkingsgewicht: 3343 g
EAN: 9783319349176