Ordered ranked set sample and applications to statistical inference

具有成本效益的抽样方法是统计学中主要关注的问题。排序集抽样（RSS）于1952年首次提出。RSS的价值在被遗忘了一段时间后，由于其具有成本效益，近年来被重新发现。现在，RSS方法引起了农业、林业、生态科学、环境科学甚至医学研究等领域的实际兴趣。到目前为止，关于秩集抽样的出版物和研究都是基于秩集样本本身或秩集样本的阶统计量的渐近性质。但在一些实际问题中，需要的不是RSS本身，而是RSS （ORSS）的阶统计量。在过去的几年中，我们成功地推导了ORSS的分布，并将其应用于一些统计推断。该建议的一部分是保持势头并探索ORSS在统计推断中的更多应用。而且，我们会将我们的工作概括为不完善的排名，这更适合实际问题。

Cost-effective sampling methods are of major concern in statistics. Ranked set sampling (RSS) was first proposed in 1952. After being forgotten for quite a while, the value of RSS was rediscovered in recent years because of its cost-effective nature. Now, RSS method attracts practical interest in areas such as agriculture, forestry, ecological science, environmental science, and even medical studies. Until recently, the publications and research about ranked set sampling are based on ranked set sample itself or on asymptotical properties of order statistics of ranked set sample. But in some practical problems, the order statistics of RSS (ORSS) other than the RSS itself are desired. In the past few years, we successfully derived the distribution of ORSS, and applied it to somce statistical inferences. Part of this proposal is to keep the momentum and to explore more applications of ORSS to statistical inference. Moreover, we will generalize our work to imperfect ranking, which is more suitable for practical problems.