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

Authors

  • Saba Riaz 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.

Keywords:

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

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.

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Published

2020-06-30

How to Cite

On the generalized class of estimators for estimation of finite population mean in the presence of non-response problem. (2020). Journal of Prime Research in Mathematics, 16(1), 52 – 63. https://jprm.sms.edu.pk/index.php/jprm/article/view/153