Asymptotic behavior of robust estimators in partially linear models with missing responses: the effect of estimating the missing probability on the simplified marginal estimators

Test ◽  
2010 ◽  
Vol 20 (3) ◽  
pp. 524-548 ◽  
Author(s):  
Ana Bianco ◽  
Graciela Boente ◽  
Wenceslao González-Manteiga ◽  
Ana Pérez-González
Keyword(s):  
Asymptotic Behavior ◽  
Linear Models ◽  
Partially Linear Models ◽  
Robust Estimators ◽  
Missing Responses ◽  
Partially Linear

Quantile Regression for Partially Linear Models with Missing Responses at Random

2015 ◽  
Vol 727-728 ◽  
pp. 1013-1016
Author(s):  
Pei Xin Zhao
Keyword(s):  
Quantile Regression ◽  
Linear Models ◽  
Estimation Method ◽  
Regression Method ◽  
Partially Linear Models ◽  
Missing Response ◽  
Missing Responses ◽  
Partially Linear ◽  
Simulation Results ◽  
Quantile Regression Method

In this paper, we propose a weighted quantile regression method for partially linear models with missing response at random. The proposed estimation method can give an efficient estimator for parametric components, and can attenuate the effect of missing responses. Some simulations are carried out to assess the performance of the proposed estimation method, and simulation results indicate that the proposed method is workable.

Robust inference in partially linear models with missing responses

2015 ◽  
Vol 97 ◽  
pp. 88-98
Author(s):  
Ana M. Bianco ◽  
Graciela Boente ◽  
Wenceslao González-Manteiga ◽  
Ana Pérez-González
Keyword(s):  
Linear Models ◽  
Robust Inference ◽  
Partially Linear Models ◽  
Missing Responses ◽  
Partially Linear
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