Research Article
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.
References
- Reference 1Dr.Zahoor AhmedReference 2Dr.Zafer Iqbal
Year 2019,
, 1045 - 1058, 01.09.2019
Abstract
References
- Reference 1Dr.Zahoor AhmedReference 2Dr.Zafer Iqbal
There are 1 citations in total.
Details
| Primary Language | English |
|---|---|
| Subjects | Engineering |
| Journal Section | Statistics |
| Authors | |
| Publication Date | September 1, 2019 |
| Published in Issue | Year 2019 |