中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Semiparametric linear transformation models for current status data

文献类型:期刊论文

作者Sun, JG; Sun, LQ
刊名CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE
出版日期2005-03-01
卷号33期号:1页码:85-96
关键词counting process current status data estimating function linear transformation models regression analysis
ISSN号0319-5724
英文摘要Current status data arise when the death of every subject in a study cannot be determined precisely, but is known only to have occurred before or after a random monitoring time. The authors discuss the analysis of such data under semiparametric linear transformation models for which they propose a general inference procedure based on estimating functions. They determine the properties of the estimates they propose for the regression parameters of the model and illustrate their technique using tumorigenicity data.
WOS研究方向Mathematics
语种英语
WOS记录号WOS:000228470300006
出版者CANADIAN JOURNAL STATISTICS
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/1086]  
专题应用数学研究所
通讯作者Sun, JG
作者单位1.Univ Missouri, Dept Stat, Columbia, MO 65211 USA
2.Chinese Acad Sci, Inst Appl Math, Beijing 100080, Peoples R China
推荐引用方式
GB/T 7714
Sun, JG,Sun, LQ. Semiparametric linear transformation models for current status data[J]. CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE,2005,33(1):85-96.
APA Sun, JG,&Sun, LQ.(2005).Semiparametric linear transformation models for current status data.CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE,33(1),85-96.
MLA Sun, JG,et al."Semiparametric linear transformation models for current status data".CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE 33.1(2005):85-96.

入库方式: OAI收割

来源:数学与系统科学研究院

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