The categorical Gini correlation is an alternative measure of dependence between categorical and numerical variables, which characterizes the independence of the variables. A non-parametric test based on the categorical Gini correlation for the equality of K distributions is developed. By applying the jackknife empirical likelihood approach, the standard limiting chi-squared distribution with degrees of freedom of K − 1 is established and is used to determine the critical value and p-value of the test. Simulation studies show that the proposed method is competitive with existing methods in terms of power of the tests in most cases. The proposed method is illustrated in an application on a real dataset.

中文翻译：

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K 样本检验的折刀经验似然法

分类基尼相关性是分类变量和数值变量之间依赖关系的另一种度量，它表征了变量的独立性。开发了一种基于分类基尼相关性的K分布相等性的非参数检验。通过应用折刀经验似然法，建立了自由度为K  -1 的标准限制卡方分布，并用于确定检验的临界值和p值。仿真研究表明，在大多数情况下，所提出的方法在测试能力方面与现有方法具有竞争力。所提出的方法在真实数据集的应用程序中进行了说明。