RATIO ESTIMATORS FOR POPULATION VARIANCE IN ADAPTIVE CLUSTER SAMPLING

Abstract

To estimate the variance for rare and cluster population has been the main problem in survey sampling. Three ratio type estimators were proposed for population variance utilizing the single auxiliary variable assuming the transformed population for adaptive cluster sampling, in presented study. The expressions for the mean square error and bias of the proposed estimator were derived. The proposed estimatorswere used to estimate the finite population variance in adaptive cluster sampling. The simulationswereperformedon a real life data to reveal and evaluate the efficiency of the estimators. The results showed that the proposed exponential ratio estimator was more efficient compared to the usual sample variance estimator and the proposed ratio type variance estimators in adaptive cluster sampling, assuming given conditions. Hence, exponential ratio estimators were recommended to estimate the population variance in adaptive cluster sampling.