Dexterous Estimation of Population Mean in Survey Sampling Under Non-Response Error
S. K. Yadav
Department of Statistics, Babasaheb Bhimrao Ambedkar University, Lucknow-226025, India.
O. P. Yadav
Department of Industrial and Manufacturing Engineering, North Dakota State University, Fargo, ND 58104, USA.
D. K. Yadav
Department of Commercial Tax, Government of Uttar Pradesh, Lucknow-226010, India.
Received on May 01, 2019
Accepted on August 05, 2019
In this scripture, we ponder the problem of efficient estimation of population mean of study variable utilizing information on highly correlated auxiliary variables under the presence of non-response on either of the variables. For this purpose, we suggest, an improved estimator under three different situations of non-response. Under the first situation, estimation of population mean is done with the problem of non-response on both the study and the auxiliary variables with the additional condition that the population means of the auxiliary variables are known. The second situation is to estimate the population mean of primary variable when the problem of non-response is only on the primary variable but the population means of the auxiliary variables are known while under the third situation estimation is performed with the problem of non-response on both the study and the auxiliary variables but population mean of one of the auxiliary variables is unknown. We study the sampling properties of the suggested estimator under above three different situations of non-response. We compare the proposed estimator with the competing estimators of population mean, under three different situations of non-response. The efficiency conditions are obtained for all three situations. A numerical study is also carried out to verify the efficiency conditions.
Keywords- Study variable, Auxiliary variable, Non-response, Bias, MSE, PRE.
Yadav, S. K., Yadav, O. P., & Yadav, D. K. (2019). Dexterous Estimation of Population Mean in Survey Sampling Under Non-Response Error. International Journal of Mathematical, Engineering and Management Sciences, 4(6), 1307-1324. https://dx.doi.org/10.33889/IJMEMS.2019.4.6-103.
Conflict of Interest
The authors have no conflict of interest regarding the publication of the article.
The authors sincerely thank anonymous reviewers and the Editor-in-Chief for providing critical comments and suggestions for improving the quality of the paper.
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