Enhancing the efficiency of the general form of estimators through Searls’ approach for population mean estimation under simple random sampling

This study focuses on enhancing the efficiency of the general form of estimators using Searls’ method [1] for estimating the population mean under simple random sampling. The proposed development builds upon the estimator introduced by Dansawad and Ketsombun [2], which encompasses several existing estimators, including those by Singh et al. [3], Gupta and Yadav [4], and Sabo et al. [5], among others. Essential statistical properties, such as the mean squared error (MSE) and the minimum mean squared error (MMSE), are derived and presented. The efficiency of the proposed general form of estimator is evaluated and compared with related estimators in terms of percentage relative efficiency (PRE). The comparative results demonstrate that the proposed estimator achieves higher efficiency than the existing estimators under identical sampling conditions.