Ordered ranked set sample and applications to statistical inference

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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.