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Linear and Generalized Linear Mixed Models and Their Applications (Springer Series in Statistics) Hardback - 2007
by Jiang, Jiming
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- Hardback
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Details
- Title Linear and Generalized Linear Mixed Models and Their Applications (Springer Series in Statistics)
- Author Jiang, Jiming
- Binding Hardback
- Edition U. S. EDITION
- Condition Used - Good
- Pages 257
- Volumes 1
- Language ENG
- Publisher Springer, New York, NY
- Publication date 2007-03-09
- Illustrated Yes
- Features Bibliography, Illustrated, Index, Table of Contents
- Bookseller's Inventory # 0387479414.G
- ISBN 9780387479415 / 0387479414
- Weight 1.12 lbs (0.51 kg)
- Dimensions 9.27 x 6.61 x 0.72 in (23.55 x 16.79 x 1.83 cm)
- Category Mathematics
- Library of Congress subjects Mathematical statistics, Linear models (Statistics)
- Library of Congress Catalogue Number 2006935876
- Dewey Decimal Code 519.5
- Quantity available 1
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From the publisher
From the rear cover
This book covers two major classes of mixed effects models, linear mixed models and generalized linear mixed models, and it presents an up-to-date account of theory and methods in analysis of these models as well as their applications in various fields. The book offers a systematic approach to inference about non-Gaussian linear mixed models. Furthermore, it has included recently developed methods, such as mixed model diagnostics, mixed model selection, and jackknife method in the context of mixed models.
The book is aimed at students, researchers and other practitioners who are interested in using mixed models for statistical data analysis. The book is suitable for a course in a M.S. program in statistics, provided that the section of further results and technical notes in each of the first four chapters is skipped. If these four sections are included, the book may be used for a course in a Ph. D. program in statistics. A first course in mathematical statistics, the ability to use computers for data analysis, and familiarity with calculus and linear algebra are prerequisites. Additional statistical courses such as regression analysis and a good knowledge about matrices would be helpful.
Jiming Jiang is Professor of Statistics and Director of the Statistical Laboratory at UC-Davis. He is a prominent researcher in the fields of mixed effects models and small area estimation, and co-receiver of the Chinese National Natural Science Award and American Statistical Association's Outstanding Statistical Application Award.
