Estimation of Gini-index from continuous distribution based on ranked set sampling

Abstract

This paper introduces the idea of using the novel ranked set sampling scheme for estimating the Gini index from continuous distributions. A one dimensional integral estimation problem based on ranked samples was discussed. It is demonstrated by a simple Monte Carlo experiment that this approach provides an unbiased and more efficient Gini index estimators than the traditional estimators based on simple random sampling.