Quantile Estimation with Auxiliary Information: Simulation Results

In this work we compare finite population quantile estimators in a simulation study. We consider settings where complete auxiliary information is available, and quantile estimators that are obtained from inversion of several well-known estimators for the population cdf. The simulation results show that estimators based on separate estimates of the regression function and the error distributions are usually the most efficient ones.