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Robust test for independence in high dimensions
Authors:Guangyu Mao
Institution:School of Economics and Management, Beijing Jiaotong University, Beijing, China
Abstract:This article develops a new test based on Spearman’s rank correlation coefficients for total independence in high dimensions. The test is robust to the non normality and heavy tails of the data, which is a merit that is not shared by the existing tests in literature. Simulation results suggest that the new test performs well under several typical null and alternative hypotheses. Besides, we employ a real data set to illustrate the use of the new test.
Keywords:High-dimensional data  higher-order moments  independence test  rank correlation
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