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The linear model and hypothesis = a general unifying theory /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	The linear model and hypothesis/ by George A.F. Seber.
Reminder of title:	a general unifying theory /
Author:	Seber, George A.F.
Published:	Cham :Imprint: Springer, : 2015.,
Description:	ix, 205 p. :ill., digital ; : 24 cm.;
Contained By:	Springer eBooks
Subject:	Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law. -
Online resource:	http://dx.doi.org/10.1007/978-3-319-21930-1
ISBN:	9783319219301

The linear model and hypothesis = a general unifying theory /
Seber, George A.F.

The linear model and hypothesisa general unifying theory /[electronic resource] :by George A.F. Seber. - Cham :Imprint: Springer,2015. - ix, 205 p. :ill., digital ;24 cm. - Springer series in statistics,0172-7397. - Springer series in statistics..

1.Preliminaries -- 2. The Linear Hypothesis -- 3.Estimation -- 4.Hypothesis Testing -- 5.Inference Properties -- 6.Testing Several Hypotheses -- 7.Enlarging the Model -- 8.Nonlinear Regression Models -- 9.Multivariate Models -- 10.Large Sample Theory: Constraint-Equation Hypotheses -- 11.Large Sample Theory: Freedom-Equation Hypotheses -- 12.Multinomial Distribution -- Appendix -- Index.

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.

ISBN: 9783319219301

Standard No.: 10.1007/978-3-319-21930-1doiSubjects--Topical Terms:

670129
Statistics for Social Science, Behavorial Science, Education, Public Policy, and Law.

LC Class. No.: QA276

Dewey Class. No.: 519.535

The linear model and hypothesis = a general unifying theory /
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505 0 $a 1.Preliminaries -- 2. The Linear Hypothesis -- 3.Estimation -- 4.Hypothesis Testing -- 5.Inference Properties -- 6.Testing Several Hypotheses -- 7.Enlarging the Model -- 8.Nonlinear Regression Models -- 9.Multivariate Models -- 10.Large Sample Theory: Constraint-Equation Hypotheses -- 11.Large Sample Theory: Freedom-Equation Hypotheses -- 12.Multinomial Distribution -- Appendix -- Index.
520 $a 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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