论文标题
使用应用
Design-based estimators of distribution function in ranked set sampling with an application
论文作者
论文摘要
许多作者都检查了基于排名集合（RSS）及其修改的经验分布函数（EDF）。在这些研究中，已经研究了提出的估计量，以针对无限的人口设置进行研究。但是，在有限人口环境中开发EDF估计器对于环境，生态，农业，生物学等领域的价值更高。本文介绍了基于RSS中的Level-0，Level-1和Level-2采样设计的新的EDF估计器。已建立了新的EDF估计量的渐近特性。在不同的分布函数下排名不完美时，已经获得了数值结果。已经观察到，与其级别0，级别1和简单的随机采样相比，级别2采样设计提供了更有效的EDF估计器。在实际数据应用中，我们考虑了分布函数的分布估计值和基于2级采样设计的RSS在七个月时在七个月时估算的绵羊中位数的估计。
Empirical distribution functions (EDFs) based on ranked set sampling (RSS) and its modifications have been examined by many authors. In these studies, the proposed estimators have been investigated for infinite population setting. However, developing EDF estimators in finite population setting would be more valuable for areas such as environmental, ecological, agricultural, biological, etc. This paper introduces new EDF estimators based on level-0, level-1 and level-2 sampling designs in RSS. Asymptotic properties of the new EDF estimators have been established. Numerical results have been obtained for the case when ranking is imperfect under different distribution functions. It has been observed that level-2 sampling design provides more efficient EDF estimator than its counterparts of level-0, level-1 and simple random sampling. In real data application, we consider a pointwise estimate of distribution function and estimation of the median of sheep's weights at seven months using RSS based on level-2 sampling design.
