On Estimation of Finite Population Variance in Double Sampling Using Auxiliary Information
This paper focuses on efficient estimation of finite population variance employing known auxiliary information in two- phase sampling scheme. We suggest, an improved and efficient generalized double sampling estimator and its sampling properties like bias and mean squared error (MSE) are derived and studied. In addition, a comparative study is also conducted to show that the propounded estimator is superior as compared to few existing estimators reported in sampling literature, thus justifying its efficiency over the competing estimators. An included numerical example confirms that the suggested generalized estimator is more precise and efficient under percent relative efficiency (PRE) criterion.
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