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A new nonparametric bivariate test for two sample location problem

机译:针对两个样本位置问题的新的非参数双变量检验

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摘要

A strictly nonparametric bivariate test for two sample location problem is proposed. The proposed test is easy to apply and does not require the stringent condition of affine-symmetry or elliptical symmetry which is required by some of the major tests available for the same problem. The power function of the proposed test is calculated. The asymptotic distribution of the proposed test statistic is found to be normal. The power of proposed test is compared with some of the well-known tests under various distributions using Monte Carlo simulation technique. The power study shows that the proposed test statistic performs better than most of the test statistics for almost all the distributions considered here. As soon as the underlying population structure deviates from normality, the ability of the proposed test statistic to detect the smallest shift in location increases as compared to its competitors. The application of the test is shown by using a data set.
机译:提出了针对两个样本位置问题的严格非参数双变量检验。所提出的测试易于应用,并且不需要针对相同问题的一些主要测试所要求的严格的仿射对称或椭圆对称条件。计算出所提议测试的幂函数。发现拟议的检验统计量的渐近分布是正态的。使用蒙特卡罗模拟技术,将所提出的测试的功能与各种分布下的一些知名测试进行了比较。功效研究表明,对于此处考虑的几乎所有分布,建议的测试统计量的性能均优于大多数测试统计量。一旦基本的人口结构偏离常态,与其竞争者相比,拟议的检验统计量检测位置最小变化的能力就会增加。通过使用数据集显示测试的应用。

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