Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/15578
Title: Jackknifing type weighted least squares estimators in partially linear regression models
Authors: You, J
Sun, X
Pang, WK
Leung, PK 
Keywords: Asymptotic covariance matrix
Consistency
Semiparametric generalized least squares estimator (SGLSE)
Issue Date: 2002
Publisher: Elsevier Science Bv
Source: Statistics and probability letters, 2002, v. 60, no. 1, p. 17-31 How to cite?
Journal: Statistics and Probability Letters 
Abstract: In a heteroskedastic partially linear regression model, You and Chen (Technical Report, Department of Mathematics and Statistics, University of Regina, 2000) proposed a semiparametric generalized least squares estimator (SGLSE). In this paper, a jackknife-type estimator of the asymptotic covariance matrix of the SGLSE is proposed. It is shown that this jackknife-type estimator is consistent and performs better than the usual δ method in some cases.
URI: http://hdl.handle.net/10397/15578
ISSN: 0167-7152
DOI: 10.1016/S0167-7152(02)00242-0
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