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Linear and generalized linear mixed ...
~
Jiang, Jiming.
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Linear and generalized linear mixed models and their applications
紀錄類型:
書目-電子資源 : Monograph/item
正題名/作者:
Linear and generalized linear mixed models and their applications/ by Jiming Jiang, Thuan Nguyen.
作者:
Jiang, Jiming.
其他作者:
Nguyen, Thuan.
出版者:
New York, NY :Springer New York : : 2021.,
面頁冊數:
xiv, 343 p. :ill., digital ;24 cm.
內容註:
1. Linear Mixed Models: Part I -- 2. Linear Mixed Models: Part II -- 3. Generalized Linear Mixed Models: Part I -- 4. Generalized Linear Mixed Models: Part II.
Contained By:
Springer Nature eBook
標題:
Linear models (Statistics) -
電子資源:
https://doi.org/10.1007/978-1-0716-1282-8
ISBN:
9781071612828
Linear and generalized linear mixed models and their applications
Jiang, Jiming.
Linear and generalized linear mixed models and their applications
[electronic resource] /by Jiming Jiang, Thuan Nguyen. - Second edition. - New York, NY :Springer New York :2021. - xiv, 343 p. :ill., digital ;24 cm. - Springer series in statistics,0172-7397. - Springer series in statistics..
1. Linear Mixed Models: Part I -- 2. Linear Mixed Models: Part II -- 3. Generalized Linear Mixed Models: Part I -- 4. Generalized Linear Mixed Models: Part II.
Now in its second edition, 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. It offers a systematic approach to inference about non-Gaussian linear mixed models. Furthermore, it discusses the latest developments and methods in the field, incorporating relevant updates since publication of the first edition. These include advances in high-dimensional linear mixed models in genome-wide association studies (GWAS), advances in inference about generalized linear mixed models with crossed random effects, new methods in mixed model prediction, mixed model selection, and mixed model diagnostics. This book is suitable for students, researchers, and practitioners who are interested in using mixed models for statistical data analysis with public health applications. It is best for graduate courses in statistics, or for those who have taken a first course in mathematical statistics, are familiar with using computers for data analysis, and have a foundational background in calculus and linear algebra.
ISBN: 9781071612828
Standard No.: 10.1007/978-1-0716-1282-8doiSubjects--Topical Terms:
533190
Linear models (Statistics)
LC Class. No.: QA276 / .J536 2021
Dewey Class. No.: 519.535
Linear and generalized linear mixed models and their applications
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