Some improved and alternative imputation methods for finite population mean in presence of missing information

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作者：
Singh, Garib Nath [1 ]
Pandey, Awadhesh K. [1 ]
Sharma, Anup Kumar [2 ]
机构：
[1] Department of Mathematics & Computing, Indian Institute of Technology (Indian School of Mines), Dhanbad, India
[2] Department of Mathematics, National Institute of Technology Raipur, Raipur, India
来源：
Communications in Statistics - Theory and Methods | 2021年 / 50卷 / 19期
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摘要：
The crux of this study is to propose some modified and improved compromised imputation methods and their corresponding point estimators to estimate the population mean using information on an auxiliary variable in case of missing data problem under simple random sampling without replacement scheme. The properties of the suggested estimation procedures have been examined. Monte Carlo simulation study has been performed in order to show that the proposed class of estimators give better results in comparison to some of the existing estimators. Suitable recommendations are made to the survey practitioners. © 2020 Taylor & Francis Group, LLC.
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页码：4401 / 4427
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