TITLE:
A New Regression Type Estimator with Two Auxiliary Variables for Single-Phase Sampling
AUTHORS:
Everline Chemutai Tum, John Kung’u, Leo Odongo
KEYWORDS:
Regression Estimator, Exponential Ratio-Product Estimator, Auxiliary Variables, Mean Squared Error
JOURNAL NAME:
Open Journal of Statistics,
Vol.4 No.9,
October
29,
2014
ABSTRACT: In this paper, we have proposed an estimator of finite population mean using a new regression type estimator with two auxiliary variables for single-phase sampling and investigated its finite sample properties. An empirical study has been carried out to compare the performance of the proposed estimator with the existing estimators that utilize auxiliary variables for finite population mean. It has been found that the new regression type estimator with two auxiliary variables for to be more efficient than mean per unit, ratio and product estimator and exponential ratio and exponential product estimators and exponential ratio-product estimator.