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Rukhin's uniformity test based on sample quantiles

机译:基于样本分位数的Rukhin均匀性测试

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摘要

The problem of testing if a given probability distribution fits to a set of independent and identically distributed observations is usually treated by categorizing the data range. Discretization can be done by means of relative frequencies or by using sample quantiles. In this article, quantile-based test statistics are proposed to test the hypothesis of uniformity in the interval (0, 1). Exact critical values of the family of Rukhin's statistics are estimated. A Monte Carlo simulation experiment is carried out to calculate powers of these tests in different alternatives. Results obtained from each kind of categorization are compared to give several recommendations about the use of Rukhin's statistics and type of categorization.
机译:通常通过对数据范围进行分类来处理测试给定概率分布是否适合一组独立且均等分布的观测值的问题。离散化可以通过相对频率或样本分位数来完成。在本文中,提出了基于分位数的检验统计量以检验区间(0,1)中的均匀性假设。估算了Rukhin统计数据的确切临界值。进行了蒙特卡洛模拟实验,以计算不同替代方案中这些测试的功效。比较从每种分类获得的结果,以提供有关Rukhin统计数据的使用和分类类型的一些建议。

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