Improvement on Estimating Quantiles in Finite Population Using Indirect Methods of Estimation

Abstract

New methods for estimating confidence limits for quantiles in a finite population are proposed. These methods use auxiliary information through the ratio, difference and regression estimator of the population distribution function. They may be applied to any type of sampling. Simulation studies based of two real populations show that the methods proposed in this paper can be considerably more efficient than the customary classic method.