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Statistical Inference on Seemingly Unrelated Single-Index Regression Models

文献类型：期刊论文

作者He, Bing1; You, Jin-hong2; Chen, Min3
刊名ACTA MATHEMATICAE APPLICATAE SINICA-ENGLISH SERIES
出版日期2016-10-01
卷号32期号:4页码:945-956
关键词seemingly unrelated contemporaneous correlation single-index weighted estimation
ISSN号0168-9673
DOI10.1007/s10255-016-0615-4
英文摘要In this article, we consider a class of seemingly unrelated single-index regression models. By taking the contemporaneous correlation among equations into account we construct the weighted estimators (WEs) for unknown parameters of the coefficients and the improved local polynomial estimators for the unknown functions, respectively. We establish the asymptotic normalities of these estimators, and show both of them are more asymptotically efficient than those ignoring the contemporaneous correlation. The performances of the proposed procedures are evaluated through simulation studies.
资助项目National Natural Science Foundation of China[11471140]
WOS研究方向Mathematics
语种英语
WOS记录号WOS:000387481600013
出版者SPRINGER HEIDELBERG
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/24132]  
专题应用数学研究所
通讯作者He, Bing
作者单位1.Jilin Univ, Sch Math, Changchun 130012, Peoples R China
2.Shanghai Univ Finance & Econ, Sch Stat & Management, Shanghai 200433, Peoples R China
3.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
推荐引用方式
GB/T 7714		 He, Bing,You, Jin-hong,Chen, Min. Statistical Inference on Seemingly Unrelated Single-Index Regression Models[J]. ACTA MATHEMATICAE APPLICATAE SINICA-ENGLISH SERIES,2016,32(4):945-956.
APA He, Bing,You, Jin-hong,&Chen, Min.(2016).Statistical Inference on Seemingly Unrelated Single-Index Regression Models.ACTA MATHEMATICAE APPLICATAE SINICA-ENGLISH SERIES,32(4),945-956.
MLA He, Bing,et al."Statistical Inference on Seemingly Unrelated Single-Index Regression Models".ACTA MATHEMATICAE APPLICATAE SINICA-ENGLISH SERIES 32.4(2016):945-956.

入库方式： OAI收割

来源：数学与系统科学研究院

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