Imputation based statistical inference for partially linear quantile regression models with missing responses

Metrika ◽  
2016 ◽  
Vol 79 (8) ◽  
pp. 991-1009 ◽  
Author(s):  
Peixin Zhao ◽  
Xinrong Tang
Keyword(s):  
Quantile Regression ◽  
Statistical Inference ◽  
Regression Models ◽  
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.

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