scholarly journals Robust inference in high-dimensional approximately sparse quantile regression models

Author(s):  
Alexandre Belloni ◽  
Victor Chernozhukov ◽  
Kengo Kato
2021 ◽  
Author(s):  
Nicolai T. Borgen ◽  
Andreas Haupt ◽  
Øyvind N. Wiborg

Using quantile regression models to estimate quantile treatment effects is becoming increasingly popular. This paper introduces the rqr command that can be used to estimate residualized quantile regression (RQR) coefficients and the rqrplot postestimation command that can be used to effortless plot the coefficients. The main advantages of the rqr command compared to other Stata commands that estimate (unconditional) quantile treatment effects are that it can include high-dimensional fixed effects and that it is considerably faster than the other commands.


2015 ◽  
Vol 88 ◽  
pp. 128-138 ◽  
Author(s):  
Mercedes Conde-Amboage ◽  
César Sánchez-Sellero ◽  
Wenceslao González-Manteiga

Biometrics ◽  
2016 ◽  
Vol 73 (2) ◽  
pp. 452-462 ◽  
Author(s):  
Youyi Fong ◽  
Chongzhi Di ◽  
Ying Huang ◽  
Peter B. Gilbert

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