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Statistical Inference on Seemingly Unrelated Single-Index Regression Models
He, Bing1; You, Jin-hong2; Chen, Min3
2016-10-01
Source PublicationACTA MATHEMATICAE APPLICATAE SINICA-ENGLISH SERIES
ISSN0168-9673
Volume32Issue:4Pages:945-956
AbstractIn 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.
Keywordseemingly unrelated contemporaneous correlation single-index weighted estimation
DOI10.1007/s10255-016-0615-4
Language英语
Funding ProjectNational Natural Science Foundation of China[11471140]
WOS Research AreaMathematics
WOS SubjectMathematics, Applied
WOS IDWOS:000387481600013
PublisherSPRINGER HEIDELBERG
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Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/24133
Collection应用数学研究所
Affiliation1.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
Recommended Citation
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.
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