An efficient exponential estimator of the mean under stratified random sampling
Tolga Zaman
Abstract
ABSTRACT Stratification of population is a probability sampling design used to increase the precision of estimation. An efficient exponential ratio estimator allows estimating the population mean in stratified random sampling using an auxiliary variable. Its expected bias, expected mean square error, and minimum mean square error are expressed. The conditions for which the estimator is more efficient are obtained. The proposed estimators under stratified random sampling have a lower mean square error than the ratio and the exponential estimators.
Topics & Concepts
Stratified samplingEstimatorStatisticsMathematicsMean squared errorRatio estimatorPopulation meanMinimum mean square errorSampling designEfficient estimatorSampling (signal processing)Exponential functionBias of an estimatorSimple random samplePoisson samplingMinimum-variance unbiased estimatorPopulationApplied mathematicsSlice samplingImportance samplingMonte Carlo methodComputer scienceMathematical analysisSociologyFilter (signal processing)DemographyComputer visionSurvey Sampling and Estimation Techniques