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D-OPTIMALITY OF GROUP TESTING FOR JOINT ESTIMATION OF CORRELATED RARE DISEASES WITH MISCLASSIFICATION

文献类型：期刊论文

作者Li, Qizhai1; Liu, Aiyi2; Xiong, Wenjun3
刊名STATISTICA SINICA
出版日期2017-04-01
卷号27期号:2页码:823-838
关键词Binary outcomes classification error D-optimal criterion group testing maximum likelihood estimate prevalence
ISSN号1017-0405
DOI10.5705/ss.202015.0178
英文摘要The D-optimal criterion is used to derive an optimality property of group testing in estimation of the prevalence of two rare correlated diseases when the disease statuses are classified with error. Exact ranges of disease prevalence are obtained in which group testing is more efficient than conventional methods of random sampling.
资助项目National Science Foundation of China[11371353] ; National Science Foundation of China[61134013] ; Breakthrough Project of Strategic Priority Program of the Chinese Academy of Sciences[XDB13040600] ; Intramural Research Program of the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) ; National Institutes of Health (NIH) ; Guangxi Natural Science Foundation[2015GXNSFBA139016]
WOS研究方向Mathematics
语种英语
WOS记录号WOS:000397365300017
出版者STATISTICA SINICA
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/25138]  
专题系统科学研究所
通讯作者Li, Qizhai
作者单位1.Chinese Acad Sci, Acad Math & Syst Sci, Key Lab Syst Control, Beijing 100190, Peoples R China
2.NICHD, Biostat & Bioinformat Branch, NIH, Bethesda, MD USA
3.Guangxi Normal Univ, Sch Math & Stat, Guilin 541004, Peoples R China
推荐引用方式
GB/T 7714		 Li, Qizhai,Liu, Aiyi,Xiong, Wenjun. D-OPTIMALITY OF GROUP TESTING FOR JOINT ESTIMATION OF CORRELATED RARE DISEASES WITH MISCLASSIFICATION[J]. STATISTICA SINICA,2017,27(2):823-838.
APA Li, Qizhai,Liu, Aiyi,&Xiong, Wenjun.(2017).D-OPTIMALITY OF GROUP TESTING FOR JOINT ESTIMATION OF CORRELATED RARE DISEASES WITH MISCLASSIFICATION.STATISTICA SINICA,27(2),823-838.
MLA Li, Qizhai,et al."D-OPTIMALITY OF GROUP TESTING FOR JOINT ESTIMATION OF CORRELATED RARE DISEASES WITH MISCLASSIFICATION".STATISTICA SINICA 27.2(2017):823-838.

入库方式： OAI收割

来源：数学与系统科学研究院

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