A family of estimators for variance estimation

Abstract

The potential of this study for estimating the finite population variance of the study variable of a class of estimators by utilizing an auxiliary variable in simple random sampling is enormous. The asymptotic properties of the proposed class of estimation procedure have been examined. The best fixed values are determined for which the mean squared error of the freshly suggested estimator is lowest. Several well-known existing estimators and class of suggested estimators are identified. To back up the theoretical results, a real population and an extensive simulation study using R software are performed, which demonstrate the dominance of the suggested estimator against all competitors. Appropriate suggestions have been made to the survey statisticians for their real-life implementation.

Keywords

• Auxiliary variable
• study variable
• simple random sampling
• bias
• mean squared error
• class of estimators