The Linear Model and Hypothesis: A General Unifying Theory

di George Seber (Autore)

Springer International Publishing AG, 2015

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.

• Autore: George Seber
• Editore: Springer International Publishing AG
• Collana: Springer Series in Statistics
• Anno: 2015
• Rilegatura: Hardback
• Pagine: 205 p.
• Dimensioni: 235 x 155 mm
• EAN: 9783319219295

Testo in English