Efficient Family of Product-Type Estimators for Mean Estimation in Successive Sampling using Auxiliary Information on Both Occasions
In this paper, we propose efficient family of product-type estimators using one auxiliary variable for the estimation of the current population mean under successive sampling scheme. This family of estimators have been studied Ray and Sahai (1980) under simple random sampling (srswor) using one auxiliary variable for estimation of the population mean. Using these estimators in successive sampling, the expression for bias and mean squared error of the proposed estimators are obtained upto the first order of approximation. Usual product estimator is identified as particular case of the suggested estimators. Optimum replacement strategy is also discussed. The proposed family of estimators at optimum condition is compared with the simple mean per unit estimator, Cochran (1977) estimator and existing other member of the family. Expressions of optimization are derived and results have been justified through empirical interpretation.
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