On optimal classes of estimators under ranked set sampling
Shashi Bhushan, Anoop Kumar
Abstract
This paper proposes some optimal classes of estimators under ranked set sampling. We have acquainted some modifications of the difference and ratio type estimators under ranked set sampling, considered by various authors like Hansen et al., Srivastava, and Walsh in simple random sampling. We have demonstrated that the efficiency of the proposed optimal classes of estimators are always better than the other existing estimators. The theoretical results have been supported by a simulation study carried out over an artificially generated population.
Topics & Concepts
EstimatorSimple random sampleMathematicsSampling (signal processing)Population meanSet (abstract data type)StatisticsExtremum estimatorRatio estimatorPopulationSimple (philosophy)M-estimatorComputer scienceEfficient estimatorMinimum-variance unbiased estimatorProgramming languageEpistemologyFilter (signal processing)SociologyDemographyPhilosophyComputer visionStatistical Distribution Estimation and ApplicationsSurvey Sampling and Estimation TechniquesAdvanced Statistical Methods and Models