Variance estimation under an efficient class of estimators in simple random sampling

This study acquaints an efficient class of estimators for variance estimation in simple random sampling. Some existing prominent estimators are established to be the particular cases of the suggested estimators. The mathematical expressions of bias and mean square error of the suggested estimators are determined to the approximation of order one. The efficacious execution of the suggested estimators is examined against all distinguished estimators available till date. Further, numerical illustrations and Monte Carlo simulations are accomplished to extend the findings of the study.