Abstract: We proposed an induced smoothingbased weighted estimator of regression parameter and an estimator of its asymptotic covariance in quantile regression model of partial covariates with random missing mechanism. We showed that the induced smoothingbased weighted estimator and empirical likelihoodbased weighted estimator had the same asymptotic covariance and the estimator of the asymptotic covariance of the induced smoothingbased weighted estimator was also consistent. We gave an efficient algorithm for calculating the induced smoothingbased weighted estimator of regression parameter and the estimator of its asymptotic covariance. Simulation results show that the proposed method performs well in finite samples.

Key words: quantile regression, missing covariates, empirical likelihoodbased weighted estimator, induced smoothing