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truncatedestimatorofasymptoticcovariancematrixinpartiallylinearmodelswithheteroscedasticerrors
Yanmeng Zhao1; Jinhong You2; Yong Zhou3
2006
Source Publicationactamathematicaeapplicataesinica
ISSN0168-9673
Volume22Issue:4Pages:565
AbstractA 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.
Language英语
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/49117
Collection应用数学研究所
Affiliation1.深圳大学
2.北卡罗来纳大学教堂山分校
3.中国科学院数学与系统科学研究院
Recommended Citation
GB/T 7714
Yanmeng Zhao,Jinhong You,Yong Zhou. truncatedestimatorofasymptoticcovariancematrixinpartiallylinearmodelswithheteroscedasticerrors[J]. actamathematicaeapplicataesinica,2006,22(4):565.
APA Yanmeng Zhao,Jinhong You,&Yong Zhou.(2006).truncatedestimatorofasymptoticcovariancematrixinpartiallylinearmodelswithheteroscedasticerrors.actamathematicaeapplicataesinica,22(4),565.
MLA Yanmeng Zhao,et al."truncatedestimatorofasymptoticcovariancematrixinpartiallylinearmodelswithheteroscedasticerrors".actamathematicaeapplicataesinica 22.4(2006):565.
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