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Linear and Generalized Linear Mixed Models and Their Applications (Springer Series in Statistics) - Hardcover
Synopsis
This book covers two major classes of mixed effects models, linear mixed models and generalized linear mixed models. 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 includes recently developed methods, such as mixed model diagnostics, mixed model selection, and jackknife method...
About the Author
Jiming Jiang is Professor of Statistics and Director of the Statistical Laboratory at UC-Davis.
Review
From the reviews:
"This book is an up to date description of linear mixed models, LMM, and generalized linear mixed models, GLMM. The material is complete enough to cover a course in a Ph.D. program in statistics. The contribution of this book is that of pointing and developing the inference and estimation issues for non-Gaussion LMMs." (Nicoleta Breaz, Zentrablatt MATH, 2009, 1152)
"The book deals with Gaussian and non-Gaussian...
"About this title" may belong to another edition of this title.
- PublisherSpringer
- Publication date2007
- ISBN 10 0387479414
- ISBN 13 9780387479415
- BindingHardcover
- LanguageEnglish
- Number of pages271
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Linear and Generalized Linear Mixed Models and Their Applications (Springer Series in Statistics)
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Linear and Generalized Linear Mixed Models and Their Applications
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Linear and Generalized Linear Mixed Models and Their Applications
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Linear and Generalized Linear Mixed Models and Their Applications
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Linear And Generalized Linear Mixed Models And Their Applications (Hb 2007)
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Linear And Generalized Linear Mixed Models And Their Applications
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