Quantile inference based on partially rank-ordered set samples

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• 作者：Omer Ozturk ; ^{omer@stat.ohio-state.edu}
• 关键词：Imperfect ranking ; Ranking models ; Median confidence interval ; Partially ranked set ; Sign test ; Judgment ranking
• 刊名：Journal of Statistical Planning and Inference
• 出版年：2012
• 期刊代码：36_03783758
• 类别：mt
• 出版时间：July, 2012
• 卷：142
• 期：7
• 页码：2116-2127
• 文件大小：251 K

摘要

This paper develops statistical inference for population quantiles based on a partially rank-ordered set (PROS) sample design. A PROS sample design is similar to a ranked set sample with some clear differences. This design first creates partially rank-ordered subsets by allowing ties whenever the units in a set cannot be ranked with high confidence. It then selects a unit for full measurement at random from one of these partially rank-ordered subsets. The paper develops a point estimator, confidence interval and hypothesis testing procedure for the population quantile of order p. Exact, as well as asymptotic, distribution of the test statistic is derived. It is shown that the null distribution of the test statistic is distribution-free, and statistical inference is reasonably robust against possible ranking errors in ranking process.