TITLE:
A New Regression Type Estimator and Its Application in Survey Sampling
AUTHORS:
M. Zahid Hasan, M. Sultana, K. Fatema, Md. Ali Hossain, M. Murad Hossain
KEYWORDS:
Auxiliary Information, Bias, Efficiency, Mean Square Error, Product and Ratio Estimator
JOURNAL NAME:
Open Journal of Statistics,
Vol.10 No.6,
December
10,
2020
ABSTRACT: In the present time, a large number of modified estimators
have been proposed by authors to obtain efficiency. In this study, we suggested
an alternative regression type estimator for estimating finite population means when there is either a positive or negative
correlation between study variables and auxiliary variables. We obtained bias
and mean square error equation of the proposed estimator ignoring the first-order approximation and
found the theoretical conditions that make proposed estimator more efficient
than simple random sampling mean estimator, product estimator and ratio
estimator. In addition, these conditions are supported by a numerical example
and it has been concluded that the proposed estimator performed better
comparing with the usual simple random sampling mean estimator, ratio estimator
and product estimator.