Improved Estimators for Simple Random Sampling and Stratified Random Sampling Under Second Order of Approximation
Improved Estimators for Simple Random Sampling and Stratified Random Sampling Under Second Order of Approximation

Summary/Abstract: Singh and Solanki (2012) and Koyuncu (2012) proposed estimators for estimating population meanY. Up to the first order of approximation and under optimum conditions, the minimum mean squared error of both the estimators is equal to the MSE of the regression estimator. In this paper, we have tried to find out the second order biases and mean square errors of these estimators using information on auxiliary variable based on simple random sampling. Finally, we have compared the performance of these estimators with some numerical illustration.

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