Open AccessModified Class of Estimator for Finite Population Mean Under Two-Phase Sampling Using Regression Estimation Approach
Author(s) -
A. Y. Erinola,
Rajesh Singh,
Ahmed Audu,
T James
Publication year - 2021
Publication title -
asian journal of probability and statistics
Language(s) - English
Resource type - Journals
ISSN - 2582-0230
DOI - 10.9734/ajpas/2021/v14i430338
Subject(s) - estimator , mean squared error , mathematics , statistics , extremum estimator , simple random sample , efficiency , population , ratio estimator , bootstrapping (finance) , population mean , efficient estimator , m estimator , econometrics , minimum variance unbiased estimator , demography , sociology
This study proposed modified a class of estimator in simple random sampling for the estimation of population mean of the study variable using as axillary information. The biases and MSE of suggested estimators were derived up to the first order approximation using Taylor’s series expansion approach. Theoretically, the suggested estimators were compared with the existing estimators in the literature. The mean square errors (MSE) and percentage relative efficiency (PRE) of proposed estimators and that of some existing estimators were computed numerically and the results revealed that the members of the proposed class of estimator were more efficient compared to their counterparts and can produce better estimates than other estimators considered in the study.