| 书目名称 | Linear and Generalized Linear Mixed Models and Their Applications |
| 编辑 | Jiming Jiang |
| 视频video | |
| 概述 | Concentrates on two major classes of mixed effects models, linear mixed models and generalized linear mixed models.Offers an up-to-date account of theory and methods in the analysis of these models as |
| 丛书名称 | Springer Series in Statistics |
| 图书封面 |  |
| 描述 | Over the past decade there has been an explosion of developments in mixed e?ects models and their applications. This book concentrates on two major classes of mixed e?ects models, linear mixed models and generalized linear mixed models, with the intention of o?ering an up-to-date account of theory and methods in the analysis of these models as well as their applications in various ?elds. The ?rst two chapters are devoted to linear mixed models. We classify l- ear mixed models as Gaussian (linear) mixed models and non-Gaussian linear mixed models. There have been extensive studies in estimation in Gaussian mixed models as well as tests and con?dence intervals. On the other hand, the literature on non-Gaussian linear mixed models is much less extensive, partially because of the di?culties in inference about these models. However, non-Gaussian linear mixed models are important because, in practice, one is never certain that normality holds. This book o?ers a systematic approach to inference about non-Gaussian linear mixed models. In particular, it has included recently developed methods, such as partially observed information, iterative weighted least squares, and jackknife in the con |
| 出版日期 | Book 20071st edition |
| 关键词 | Regression analysis; data analysis; generalized linear mixed models; linear mixed models; linear optimiz |
| 版次 | 1 |
| doi | https://doi.org/10.1007/978-0-387-47946-0 |
| isbn_ebook | 978-0-387-47946-0Series ISSN 0172-7397 Series E-ISSN 2197-568X |
| issn_series | 0172-7397 |
| copyright | Springer-Verlag New York 2007 |
发表于 2025-3-21 18:44:56
