Test for Accuracy of Ranking in Moving Extreme Ranked Set Sampling

Abstract

Moving Extreme Ranked Set Sampling (MERSS) is a variation of Ranked Set Sampling (RSS) that simplifies the technique and makes it more applicable. In MERSS, the judgment maximum of random samples of sizes 1, 2,…, are taken for actual measurement. Testing for error in ranking should be done before using the MERSS for inference. Testing whether judgment ranking is as good as actual ranking is considered in this paper. Three nonparametric tests are considered. These tests are mainly based on the distance between the actual and the judgment ranking of the obtained data. The null and the alternative distributions of the test statistics are derived. A real data set is used for illustration.