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The Local LinearM-Estimation with Missing Response Data
release_rev_d807a391-d34f-4e3a-87d6-e75f1a3636e2
by
Shuanghua Luo, Cheng-Yi Zhang, Fengmin Xu
Abstract
This paper studies the nonparametric regressive function with missing response data. Three local linear<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M2"><mml:mrow><mml:mi>M</mml:mi></mml:mrow></mml:math>-estimators with the robustness of local linear regression smoothers are presented such that they have the same asymptotic normality and consistency. Then finite-sample performance is examined via simulation studies. Simulations demonstrate that the complete-case data<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M3"><mml:mrow><mml:mi>M</mml:mi></mml:mrow></mml:math>-estimator is not superior to the other two local linear<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="M4"><mml:mrow><mml:mi>M</mml:mi></mml:mrow></mml:math>-estimators.
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