Generalized Regression-Cum-Exponential Estimators Using Two Auxiliary Variables for Population Variance in Simple Random Sampling

Abstract

In this paper, we proposed two generalized regression-cum-exponential type estimators for theestimation of finite population variance using the information of mean and variance of the auxiliaryvariables in simple random sampling (SRS). The expressions of approximate bias and mean squareerror (MSE) of the proposed estimators are derived. Many special cases of the proposed estimatorsare obtained by using different combinations of real numbers and some conventional parametersof the auxiliary variables. Algebraic comparisons of the proposed estimators have been made withsome available estimators. From the numerical study, we analyzed that the proposed estimatorsperform well than the existing estimators available in the literature.