科学研究
报告题目:

Jackknife Empirical Likelihood Approach for K-sample Tests

报告人:

Prof. Yongli Sang(University of Louisiana at Lafayette)

报告时间:

报告地点:

理学院东北楼二楼报告厅(209)

报告摘要:

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