Linear Model Methodology

Zusatztext 82970142 Informationen zum Autor André I. Khuri is a Professor Emeritus in the Department of Statistics at the University of Florida in Gainesville. Klappentext Supported by a large number of examples! this book provides a foundation in the theory of linear models and explores the developments in data analysis. It encompasses a wide variety of topics in linear models that incorporate the classical approach and other trends and modeling techniques. Zusammenfassung Supported by a large number of examples, this book provides a foundation in the theory of linear models and explores the developments in data analysis. It encompasses a wide variety of topics in linear models that incorporate the classical approach and other trends and modeling techniques. Inhaltsverzeichnis Linear Models: Some Historical Perspectives. Basic Elements of Linear Algebra. Basic Concepts in Matrix Algebra. The Multivariate Normal Distribution. Quadratic Forms in Normal Variables. Full-Rank Linear Models. Less-Than-Full-Rank Linear Models. Balanced Linear Models. The Adequacy of Satterthwaite’s Approximation. Unbalanced Fixed-Effects Models. Unbalanced Random and Mixed Models. Additional Topics in Linear Models. Generalized Linear Models. Bibliography. Index.

Dettagli sul prodotto

• Autori: Khuri Andre I., Andre I. (Professor Emeritus Khuri, Andre I. Khuri
• Editore: Taylor & Francis Ltd.
• Contenuto: Libro
• Forma del prodotto: Copertina rigida
• Data pubblicazione: 21.10.2009
• Categoria: Scienze naturali, medicina, informatica, tecnica > Matematica > Teoria delle probabilità, stocastica, statistica m; Saggistica > Psicologia, esoterismo, spiritualità, antroposofia > Psicologia: tematiche generali, opere di consultaz
• EAN: 9781584884811
• ISBN: 978-1-58488-481-1
• Numero di pagine: 562
• Categorie: MATHEMATICS / Probability & Statistics / General, Probability & statistics, Probability and statistics, statistical inference, Multivariate normal distribution, matrix algebra applications, experimental design theory, variance components analysis, advanced linear statistical methods, mixed-effects modeling