CLT of wavelet estimator in semiparametric model with correlated errors

被引:0
|
作者
Niu, Sili [1 ]
Liu, Yamei [2 ]
机构
[1] Tongji Univ, Dept Math, Shanghai 200092, Peoples R China
[2] Henan Univ Urban Construct, Dept Math & Phys, Pingdingshan 467044, Peoples R China
基金
中国国家自然科学基金;
关键词
Asymptotic normality; correlated error; negatively associated; semiparametric model; wavelet estimator; LINEAR-REGRESSION MODELS; ASYMPTOTIC NORMALITY; WEIGHTED SUMS; COMPLETE CONVERGENCE;
D O I
10.1007/s11424-012-0166-6
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
This paper considers the semiparametric regression model y (i) = x (i) beta+g(t (i) )+V (i) (1 a parts per thousand currency sign i a parts per thousand currency sign n), where (x (i) , t (i) ) are known design points, beta is an unknown slope parameter, g(center dot) is an unknown function, the correlated errors with , and e (i) are negatively associated random variables. Under appropriate conditions, the authors study the asymptotic normality for wavelet estimators of beta and g(center dot). A simulation study is undertaken to investigate finite sample behavior of the estimators.
引用
收藏
页码:567 / 581
页数:15
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