OPEN ACCESS OJS Exponential Ratio Type Estimators of Population Mean under Non-Response

Abstract

Copyright © 2014 Lovleen Kumar Grover, Parmdeep Kaur. 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. In accordance of the Creative Commons Attribution License all Copyrights © 2014 are reserved for SCIRP and the owner of the intellectual property Lovleen Kumar Grover, Parmdeep Kaur. All Copyright © 2014 are guarded by law and by SCIRP as a guardian. This paper proposes some exponential ratio type estimators of population mean under the situations when cer-tain observations for some sampling units are missing. These missing observations may be for either auxiliary variable or study variable. The biases and mean square errors of the proposed estimators have been derived, up to the first order of approximation. The proposed estimators are compared theoretically with that of the existing ratio type estimators defined by [1]. It has been found that the proposed exponential ratio type estimators per-form better than the mean per unit estimator even for the low positive correlation between study variable and auxiliary variable. Moreover, we obtained the conditions for which our proposed estimators are better than the corresponding ratio type estimators of [1]. To verify the theoretical results obtained, a simulation study is car-ried out finally