The Linear Model and Hypothesis - George Seber

The Linear Model and Hypothesis

A General Unifying Theory

(Autor)

Buch | Softcover
IX, 205 Seiten
2016 | 1. Softcover reprint of the original 1st ed. 2015
Springer International Publishing (Verlag)
978-3-319-34917-6 (ISBN)
53,49 inkl. MwSt
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.

George Seber is an Emeritus Professor of Statistics at Auckland University, New Zealand. He is an elected Fellow of the Royal Society of New Zealand, recipient of their Hector medal in Information Science, and recipient of an international Distinguished Statistical Ecologist Award. He has authored or coauthored 16 books and 90 research articles on a wide variety of topics including linear and nonlinear models, multivariate analysis, matrix theory for statisticians, large sample theory, adaptive sampling, genetics, epidemiology, and statistical ecology.

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.

"The book deals with the classical topic of multivariate linear models. ... the monograph is a consistent, logical and comprehensive treatment of the theory of linear models aimed at scientists who already have a good knowledge of the subject and are well trained in application of matrix algebra." (Jurgita Markeviciute, zbMATH 1371.62002, 2017)

"This monograph is a welcome update of the author's 1966 book. It contains a wealth of material and will be of interest to graduate students, teachers, and researchers familiar with the 1966 book." (William I. Notz, Mathematical Reviews, June, 2016)

Erscheinungsdatum
Reihe/Serie Springer Series in Statistics
Zusatzinfo IX, 205 p.
Verlagsort Cham
Sprache englisch
Maße 155 x 235 mm
Gewicht 338 g
Themenwelt Mathematik / Informatik Mathematik Wahrscheinlichkeit / Kombinatorik
Sozialwissenschaften Soziologie Empirische Sozialforschung
Schlagworte Analysis of Variance • Goodness-of-fit test. • Hypothesis tests • Lagrange multiplier test • Large sample tests • likelihood ratio test • linear models • Missing observations • Multinomial distribution • Multivariate hypothesis testing • orthogonal projections • Score test • Separable hypotheses • Simultaneous confidence intervals • Wald test
ISBN-10 3-319-34917-1 / 3319349171
ISBN-13 978-3-319-34917-6 / 9783319349176
Zustand Neuware
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