Weighted Graph-Based Two-Sample Test via Empirical Likelihood

Xiaofeng Zhao and Mingao Yuan ()
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Xiaofeng Zhao: School of Mathematics and Statistics, North China University of Water Resources and Electric Power, Zhengzhou 450045, China
Mingao Yuan: Department of Statistics, North Dakota State University, Fargo, ND 58103, USA

Mathematics, 2024, vol. 12, issue 17, 1-15

Abstract: In network data analysis, one of the important problems is determining if two collections of networks are drawn from the same distribution. This problem can be modeled in the framework of two-sample hypothesis testing. Several graph-based two-sample tests have been studied. However, the methods mainly focus on binary graphs, and many real-world networks are weighted. In this paper, we apply empirical likelihood to test the difference in two populations of weighted networks. We derive the limiting distribution of the test statistic under the null hypothesis. We use simulation experiments to evaluate the power of the proposed method. The results show that the proposed test has satisfactory performance. Then, we apply the proposed method to a biological dataset.

Keywords: two-sample test; weighted graph; empirical likelihood (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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