mean estimation using robust quantile regression with two auxiliary variables

In the presence of outliers in the data set, the utilization of robust regression tools for mean estimationis a widely established practice in survey sampling with single auxiliary variable. abid et al. (2018),with the aid of some non-conventional location measures and traditional ols, proposed a class of meanestimators using information on two supplementary variates under a simple random sampling framework. the utilization of non-traditional measures of location, especially in the presence of outliers,performed better than existing conventional estimators. in this study, we have proposed a new class ofestimators of mean utilizing quantile regression. the general forms of mse and mmse are also derived.the theoretical findings are being reinforced by different real-life data sets and simulation study.