Combined Exponential-Type Estimators for Finite Population Mean in Two-Phase Sampling

Abstract

A family of exponential-type estimator for estimating population mean in two-phase sampling when the population proportion of the auxiliary character is available is proposed in this paper. Theoretically, the bias and minimum mean square error (MSE) for the proposed estimator are obtained. The expression for MSE of the proposed exponential-type of estimator is compared with the existing estimators in the literature. The optimum values of the parameters are determined. An empirical study was carried out by comparing the proposed estimators with some of the existing estimators reviewed in the literature based on the criteria of bias, mean square error (MSE) and relative efficiency using life datasets. The result of the comparisons showed that the proposed exponential-type estimators produce a better estimate of finite population mean than the existing estimators in the sense of having higher percentage relative efficiency which implies lesser mean square error and bias. Furthermore, the realistic conditions under which the proposed class of exponential-type estimators is more efficient were also presented. Thus, the proposed estimators can be considered as significant alternatives to estimating population characteristics of real life datasets.

A Generalized Approach for Estimation of a Finite Population Mean in Two-Phase Sampling

“…Considering the utility of two-phase sampling, various scientists and researchers have made their valuable contributions by formulating estimators for the population mean on utilizing the ratio, product and regression methods (for instance, Sukhatme [2], Srivastava [3], Sisodia and Dwivedi [4], Diana and Tommasi [5], Singh and Ruiz Espejo [6], Handique [7], Malik and Tailor [8], Vishwakarma and Kumar [9], Kumar and Vishwakarma [10], Kumar and Tiwari [11], Erinola et al [12], Kumar and Tiwari [13] and Oyeyemi et al [14].…”

Estimation of finite population mean using double sampling under probability proportional to size sampling in the presence of extreme values

“…in the context of stratified two-stage sampling, we talked about exponential chain ratio estimators [ 30 ]. consuming two auxiliary information in stratified two-phase sampling, a new, more accurate calibration estimator was presented [ 31 ]. recommended a family of estimators for predicting population mean from auxiliary proportions in single- and two-stage samples [ 32 ].…”

Modified Estimator of Finite Population Variance under Stratified Random Sampling

“…Researchers have been considering the use of auxiliary information in various forms to construct more accurate estimators for population parameters in experimental surveys. This approach has been shown to significantly improve the accuracy of the population mean estimation, and it has been explored by several researchers, including [1][2][3]. The field of survey sampling has seen a significant amount of research devoted to developing estimators of population variance to measure variations that exist in real-world scenarios.…”