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1. Jackknifing type weighted least squares estimators in partially linear regression models

Author

You, Jinhong, Sun, Xiaoqian, Pang, Wan-kai, and Leung, Ping-kei

Subjects
*LEAST squares, *ANALYSIS of covariance
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. [Copyright &y& Elsevier]

Published
2002
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