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The Linear Model and Hypothesis

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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 involvematrix 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 to other models in the analysis of variance, and to show that the asymptotic equivalence of the likelihood ratio, Wald, and Score (Lagrange Multiplier) hypothesis tests generally applies.

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Detail Information

Series Title

Springer Series in Statistics

Call Number

-

Publisher

Springer Cham : Springer Cham., 2015

Collation

IX, 205

Language

English

ISBN/ISSN

978-3-319-21930-1

Classification

NONE

Content Type

text

Media Type

computer

Carrier Type

-

Edition

-

Subject(s)

Public Policy

Specific Detail Info

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Statement of Responsibility

George Seber

Other Information

Cataloger

Jemadi

Source

https://link.springer.com/book/10.1007/978-3-319-21930-1

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