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Thursday, May 30
Computational Statistics
Computationally Intensive Methods: Resampling and MCMC
Thu, May 30, 1:30 PM - 3:05 PM
Grand Ballroom K

Jackknife Empirical Likelihood Approach for K-Sample Tests via Energy Distance (305116)

*Yongli Sang, University of Louisiana at Lafayette 

Keywords: Energy distance, K-sample test, Jackknife empirical likelihood, U-statistic, Wilks' theorem, Power

Energy distance is a statistical distance between the distributions of random variables, which characterizes the equality of the distributions. Utilizing the energy distance, we develop a nonparametric test for the equality of K (K>= 2) distributions in this talk. 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 our 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.