On the generalized class of estimators for estimation of finite population mean in the presence of non-response problem

Saba Riaz\(^1\)
Department of Computer Science, SZABIST, Islamabad, Pakistan.
Amna Nazeer
Department of Mathematics, COMSATS University Islamabad, Pakistan.
Javeria Abbasi
Department of Mathematics, COMSATS University Islamabad, Pakistan.
Sadia Qamar
Department of Statistics, University of Sargodha, Pakistan.
\(^{1}\)Corresponding Author: sabaqau@gmail.com
Copyright © 2020 Saba Riaz, Amna Nazeer, Javeria Abbasi, Sadia Qamar. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Submitted: 20 August 2019; Accepted: 12 December 2019; Published: 19 March 2020.

Abstract

This work considers a generalized class of biased estimators for the estimation of the unknown population mean of the variable of interest accompanying the issue of non-response in the study and in the auxiliary variables. The asymptotic bias and the asymptotic variance of the suggested class are acquired, up to the first degree of approximation and, compared with the linear regression estimator. The efficiency of the suggested estimators while comparing with the linear regression estimator and some other existing estimators are studied regarding percent relative efficiency (PRE). Furthermore, a simulation study also affirms the excellence of the considered class of estimators.

Keywords:

Biased estimators, incomplete information, linear regression estimator, simulation, efficacy.