Imputation of missing data using multi auxiliary information under ranked set sampling

被引:8
|
作者
Bhushan, Shashi [1 ]
Kumar, Anoop [2 ,3 ]
机构
[1] Univ Lucknow, Dept Stat, Lucknow, India
[2] Amity Univ Uttar Pradesh, Amity Sch Appl Sci, Dept Stat, Lucknow, India
[3] Amity Univ Uttar Pradesh, Amity Sch Appl Sci, Dept Stat, Lucknow 226028, India
关键词
Imputation; Missing data; Ranked set sampling;
D O I
10.1080/03610918.2023.2288796
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
In this paper, we intend to utilize the multi auxiliary information available under RSS for the imputation of missing data. The mean imputation, regression imputation methods, and power transformation imputation method are identified as special cases of the proposed imputation methods. These methods are dominated by the proposed imputation methods. The theoretical comparison provides the dominance conditions of the proposed imputation methods over their conventional counterparts. In support of the theoretical findings, a simulation study is considered over a hypothetically generated population. Furthermore, some real data examples are also provided to generalize the simulation results.
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页数:22
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