Block empirical likelihood for longitudinal partially linear regression models
文献类型：期刊论文
| 作者 | You, JH; Chen, GM; Zhou, Y
|
| 刊名 | CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE
 |
| 出版日期 | 2006-03-01 |
| 卷号 | 34期号:1页码:79-96 |
| 关键词 | block empirical likelihood confidence region longitudinal data partially linear regression model semiparametric inference Wilks theorem |
| ISSN号 | 0319-5724 |
| 英文摘要 | The authors propose a block empirical likelihood procedure to accommodate the within-group correlation in longitudinal partially linear regression models. This leads them to prove a nonparametric version of the Wilks theorem. In comparison with normal approximations, their method does not require a consistent estimator for the asymptotic covariance matrix, which makes it easier to conduct inference on the parametric component of the model. An application to a longitudinal study on fluctuations of progesterone level in a menstrual cycle is used to illustrate the procedure developed here. |
| WOS研究方向 | Mathematics |
| 语种 | 英语 |
| WOS记录号 | WOS:000237203900006 |
| 出版者 | CANADIAN JOURNAL STATISTICS |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/3299]  |
| 专题 | 应用数学研究所 |
| 通讯作者 | You, JH |
| 作者单位 | 1.Univ N Carolina, Dept Biostat, Chapel Hill, NC 27599 USA 2.Univ Calgary, Dept Math & Stat, Calgary, AB T2N 1N4, Canada 3.Chinese Acad Sci, Inst Appl Math, Acad Math & Syst Sci, Beijing 100080, Peoples R China |
| 推荐引用方式 GB/T 7714 | You, JH,Chen, GM,Zhou, Y. Block empirical likelihood for longitudinal partially linear regression models[J]. CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE,2006,34(1):79-96. |
| APA | You, JH,Chen, GM,&Zhou, Y.(2006).Block empirical likelihood for longitudinal partially linear regression models.CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE,34(1),79-96. |
| MLA | You, JH,et al."Block empirical likelihood for longitudinal partially linear regression models".CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE 34.1(2006):79-96. |
入库方式： OAI收割
来源：数学与系统科学研究院
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