The Linear Model and Hypothesis

George Seber

ISBN 10: 3319219294 / ISBN 13: 9783319219295

Editore: Springer International Publishing, Springer Nature Switzerland Okt 2015, 2015

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This item is printed on demand - it takes 3-4 days longer - Neuware -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. 216 pp. Englisch.

Codice articolo 9783319219295

Dati bibliografici

• Titolo: The Linear Model and Hypothesis
• Editore: Springer International Publishing, Springer Nature Switzerland Okt 2015
• Data di pubblicazione: 2015
• Lingua: Inglese
• ISBN 10: 3319219294
• ISBN 13: 9783319219295
• Rilegatura: Buch
• Condizione: Neu
• Dimensioni: 241 L x 160 A x 16 P (millimetri) 241 millimetri di larghezza per 160 millimetri di altezza per 16 millimetri di profondità
• Peso: 494 grammi

Descrizione articolo

Riassunto

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.

Informazioni sull'autore

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.