Local likelihood with time-varying additive hazards model
文献类型：期刊论文
| 作者 | Li, Hui; Yin, Guosheng; Zhou, Yong
|
| 刊名 | CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE
 |
| 出版日期 | 2007-06-01 |
| 卷号 | 35期号:2页码:321-337 |
| 关键词 | additive model asymptotic normality censored data local polynomial maximum likelihood nonparametric estimation |
| ISSN号 | 0319-5724 |
| 英文摘要 | The authors propose the local likelihood method for the time-varying coefficient additive hazards model. They use the Newton-Raphson algorithm to maximize the likelihood into which a local polynomial expansion has been incorporated. They establish the asymptotic properties for the time-varying coefficient estimators and derive explicit expressions for the variance and bias. The authors present simulation results describing the performance of their approach for finite sample sizes. Their numerical comparisons show the stability and efficiency of the local maximum likelihood estimator. They finally illustrate their proposal with data,from a laryngeal cancer clinical study. |
| WOS研究方向 | Mathematics |
| 语种 | 英语 |
| WOS记录号 | WOS:000247847200008 |
| 出版者 | CANADIAN JOURNAL STATISTICS |
| 源URL | [http://ir.amss.ac.cn/handle/2S8OKBNM/4533]  |
| 专题 | 应用数学研究所 |
| 通讯作者 | Li, Hui |
| 作者单位 | 1.Beijing Normal Univ, Sch Math Sci, Beijing 100875, Peoples R China 2.MD Anderson Canc Ctr, Dept Biostat, Houston, TX 77030 USA 3.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100080, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Hui,Yin, Guosheng,Zhou, Yong. Local likelihood with time-varying additive hazards model[J]. CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE,2007,35(2):321-337. |
| APA | Li, Hui,Yin, Guosheng,&Zhou, Yong.(2007).Local likelihood with time-varying additive hazards model.CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE,35(2),321-337. |
| MLA | Li, Hui,et al."Local likelihood with time-varying additive hazards model".CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE 35.2(2007):321-337. |
入库方式： OAI收割
来源：数学与系统科学研究院
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