| Truncated Estimator of Asymptotic Covariance Matrix in Partially Linear Models with Heteroscedastic Errors |
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| 引用本文： | Yan-meng Zhao Jin-hong You Yong Zhou. Truncated Estimator of Asymptotic Covariance Matrix in Partially Linear Models with Heteroscedastic Errors[J]. 应用数学学报(英文版), 2006, 22(4): 565-574. DOI: 10.1007/s10255-006-0330-7 |
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| 作者姓名： | Yan-meng Zhao Jin-hong You Yong Zhou |
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| 作者单位： | [1]Department of Mathematics, Shenzhen University, Shenzhen 518060, China [2]Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7400, USA [3]Center for Statistical Research, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100080, China |
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| 基金项目： | Zhou＇s research was partially supported by the National Natural Science Foundation of China （No.10471140, 10571169） |
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| 摘 要： | A partially linear regression model with heteroscedastic and/or serially correlated errors is studied here. It is well known that in order to apply the semiparametric least squares estimation （SLSE） to make statistical inference a consistent estimator of the asymptotic covariance matrix is needed. The traditional residual-based estimator of the asymptotic covariance matrix is not consistent when the errors are heteroscedastic and/or serially correlated. In this paper we propose a new estimator by truncating, which is an extension of the procedure in White. This estimator is shown to be consistent when the truncating parameter converges to infinity with some rate.
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| 关 键 词： | 部分线性消退模型 异方差 连续相关性 准参最小平方估计 渐近协方差矩阵 |
| 收稿时间： | 2005-10-25 |
| 修稿时间： | 2005-10-252006-06-01 |
Truncated Estimator of Asymptotic Covariance Matrix in Partially Linear Models with Heteroscedastic Errors |
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| Yan-meng Zhao,Jin-hong You,Yong Zhou. Truncated Estimator of Asymptotic Covariance Matrix in Partially Linear Models with Heteroscedastic Errors[J]. Acta Mathematicae Applicatae Sinica, 2006, 22(4): 565-574. DOI: 10.1007/s10255-006-0330-7 |
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| Authors: | Yan-meng Zhao Jin-hong You Yong Zhou |
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| Affiliation: | (1) Department of Mathematics, Shenzhen University, Shenzhen, 518060, China;(2) Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-7400, USA;(3) Center for Statistical Research, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, 100080, China |
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| Abstract: | A partially linear regression model with heteroscedastic and/or serially correlated errors is studied here.It is well known that in order to apply the semiparametric least squares estimation (SLSE) to make statistical inference a consistent estimator of the asymptotic covariance matrix is needed.The traditional residual-based estimator of the asymptotic covariance matrix is not consistent when the errors are heteroscedastic and/or serially correlated.In this paper we propose a new estimator by truncating,which is an extension of the procedure in White.This estimator is shown to be consistent when the truncating parameter converges to infinity with some rate. |
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| Keywords: | Partially linear regression model heteroscedastic serially correlation semiparametric least squares estimation asymptotic covariance matrix |
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