Generalized Profile LSE in Varying-Coefficient Partially Linear Models with Measurement Errors
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|
作者:
Yun-bei MA
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机构:
School of Statistics,Southwestern University of Finance and EconomicsSchool of Statistics,Southwestern University of Finance and Economics
Yun-bei MA
[1
]
Jin-hong YOU
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机构:
School of Statistics and Management,Shanghai University of Finance and EconomicsSchool of Statistics,Southwestern University of Finance and Economics
Jin-hong YOU
[2
]
Yong ZHOU
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机构:
School of Statistics and Management,Shanghai University of Finance and Economics
Academy of Mathematics and System Sciences,Chinese Academy of SciencesSchool of Statistics,Southwestern University of Finance and Economics
Yong ZHOU
[2
,3
]
机构:
[1] School of Statistics,Southwestern University of Finance and Economics
[2] School of Statistics and Management,Shanghai University of Finance and Economics
[3] Academy of Mathematics and System Sciences,Chinese Academy of Sciences
Semiparametric modeling;
varying-coefficient;
measurement error;
local polynomial;
profile least squares;
asymptotic normality;
D O I:
暂无
中图分类号:
O212.1 [一般数理统计];
学科分类号:
020208 ;
070103 ;
0714 ;
摘要:
This paper is concerned with the estimating problem of a semiparametric varying-coefficient partially linear errors-in-variables model Yi=Xτiβ+Zτiα(Ui)+εi , Wi=Xi+ξi,i=1, ··· , n. Due to measurement errors, the usual profile least square estimator of the parametric component, local polynomial estimator of the nonparametric component and profile least squares based estimator of the error variance are biased and inconsistent. By taking the measurement errors into account we propose a generalized profile least squares estimator for the parametric component and show it is consistent and asymptotically normal. Correspondingly, the consistent estimation of the nonparametric component and error variance are proposed as well. These results may be used to make asymptotically valid statistical inferences. Some simulation studies are conducted to illustrate the finite sample performance of these proposed estimations.
机构:
Shanghai Maritime Univ, Dept Math, Shanghai, Peoples R ChinaShanghai Maritime Univ, Dept Math, Shanghai, Peoples R China
Xu, Hong-Xia
Fan, Guo-Liang
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机构:
Shanghai Maritime Univ, Sch Econ & Management, Shanghai, Peoples R China
Renmin Univ China, Inst Stat & Big Data, Beijing, Peoples R ChinaShanghai Maritime Univ, Dept Math, Shanghai, Peoples R China
Fan, Guo-Liang
Wu, Cheng-Xin
论文数: 0引用数: 0
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机构:
Huangshan Univ, Sch Math & Stat, Huangshan, Peoples R ChinaShanghai Maritime Univ, Dept Math, Shanghai, Peoples R China
Wu, Cheng-Xin
Chen, Zhen-Long
论文数: 0引用数: 0
h-index: 0
机构:
Zhejiang Gongshang Univ, Sch Stat & Math, Hangzhou, Zhejiang, Peoples R ChinaShanghai Maritime Univ, Dept Math, Shanghai, Peoples R China
机构:
Beijing Univ Technol, Coll Appl Sci, Beijing 100124, Peoples R China
Shanxi Normal Univ, Sch Math & Comp Sci, Linfen 041000, Peoples R ChinaBeijing Univ Technol, Coll Appl Sci, Beijing 100124, Peoples R China
Yu, Ping
Du, Jiang
论文数: 0引用数: 0
h-index: 0
机构:
Beijing Univ Technol, Coll Appl Sci, Beijing 100124, Peoples R China
Collaborat Innovat Ctr Capital Social Construct &, Beijing 100124, Peoples R ChinaBeijing Univ Technol, Coll Appl Sci, Beijing 100124, Peoples R China
Du, Jiang
Zhang, Zhongzhan
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h-index: 0
机构:
Beijing Univ Technol, Coll Appl Sci, Beijing 100124, Peoples R China
Collaborat Innovat Ctr Capital Social Construct &, Beijing 100124, Peoples R ChinaBeijing Univ Technol, Coll Appl Sci, Beijing 100124, Peoples R China
机构:
Hong Kong Polytech Univ, Dept Math Appl, Kowloon, Hong Kong, Peoples R ChinaHong Kong Polytech Univ, Dept Math Appl, Kowloon, Hong Kong, Peoples R China
Zhou, X
You, JH
论文数: 0引用数: 0
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机构:Hong Kong Polytech Univ, Dept Math Appl, Kowloon, Hong Kong, Peoples R China