Open AccessAn Alternative Class of Ratio-Regression-Type Estimator under Two-Phase Sampling Scheme
Author(s) -
Isah Muhammad,
Yahaya Zakari,
Ahmed Audu
Publication year - 2022
Publication title -
cbn journal of applied statistics
Language(s) - English
Resource type - Journals
ISSN - 2476-8472
DOI - 10.33429/cjas.12221.1/5
Subject(s) - estimator , ratio estimator , mathematics , mean squared error , statistics , efficient estimator , bias of an estimator , consistent estimator , minimum variance unbiased estimator , econometrics
In this study, a new exponential ratio-regression estimator is developed using an auxiliary variable for estimating the finite population mean under a two-phase sampling system. The Bias and Mean Square Error (MSE) of the proposed estimator are derived and compared with some of the estimators in extant literature. Thus, the conditions under which the proposed estimator is better than some existing estimators are provided. Empirically, using four real datasets and simulation study, the proposed estimator performs better than the classical ratio, classical regression, exponential ratio, and exponential regression cum ratio estimator when compared using the criteria of bias, mean square error and percentage relative efficiency. The proposed estimator can be used to estimate the averages of economic variables such as inflation, exchange rate, and standard of living for policy formulation.