LAUSR

In the presence of outliers in the data set, the utilization of robust regression tools for mean estimation is a widely established practice in survey sampling with single auxiliary variable. Abid et al. [1], with the aid of some non-conventional location measures and traditional OLS, proposed a class of mean estimators 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 of estimators 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.