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Abstract：
Ranked set sampling (RSS) is known to increase the efficiency of the estimators while comparing it with simple random sampling. The problem of missingness creates a gap in the information that needs to be addressed before proceeding for estimation. Negligible amount of work has been carried out to deal with missingness utilizing RSS. This paper proposes some logarithmic type methods of imputation for the estimation of population mean under RSS using auxiliary information. The properties of the suggested imputation procedures are examined. A simulation study is accomplished to show that the proposed imputation procedures exhibit better results in comparison to some of the existing imputation procedures. Few real applications of the proposed imputation procedures is also provided to generalize the simulation study.
摘要：
已知排序集采样（RSS）可以提高估计器的效率，同时将其与简单的随机抽样进行比较。错误的问题在继续进行估计之前需要解决的信息中造成了差距。已经进行了少量的工作来处理利用RSS的错误。本文提出了一些利用辅助信息估计RSS下总体均值的对数型插补方法。检查了建议的估算程序的属性。完成了仿真研究，以表明与某些现有的插补程序相比，所提出的插补程序具有更好的结果。还提供了所提出的插补程序的实际应用来概括仿真研究。
