Abstract
In this paper, we propose the penalized weighted composite quantile regression estimation for linear model when the covariates are missing at random. Under some mild conditions, the asymptotic normality, oracle property and Horvitz–Thompson property of the proposed estimators are established. Simulation results and a real data analysis are provided to examine the performance of our methods.
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