Classes of Population Mean Estimators using Transformed Variables in Double Sampling

Transformation techniques have been used to increase the efficiency of estimators in sample surveys. In this paper, some classes of population mean estimators using transformation on an auxiliary variable and on both the auxiliary and study variables have been proposed under double sampling. We obtain the biases and mean square errors of the proposed estimators up to the first order of approximation. A simulation study and application to a rubber production dataset have been used to illustrate the performance of the proposed estimators. The results show that the proposed estimators perform much better than other existing estimators under given conditions.