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 the estimation of finite population variance using the information of mean and variance of the auxiliary variables in simple random sampling (SRS). The expressions of approximate bias and mean square error (MSE) of the proposed estimators are derived. Many special cases of the proposed estimators are obtained by using different combinations of real numbers and some conventional parameters of the auxiliary variables. Algebraic comparisons of the proposed estimators have been made with some available estimators. From the numerical study, we analyzed that the proposed estimators perform well than the existing estimators available in the literature.

Keywords

• Auxiliary Information,, Exponential Estimators

References

1. Reference 1Dr.Zahoor AhmedReference 2Dr.Zafer Iqbal