A Permutation Test for High-Dimensional Covariance Matrix

Abstract

In the case of “big p and small n”, classical statistical methods and theories are difficult to apply to high-dimensional data problems. This article considers testing the equality of two sample covariance matrices. When both the dimension p and the sample size n tend to infinity, a permutation method is proposed. The new test method eliminates the limitation of sample distribution and dimension. Numerical research shows that the proposed test method has good results in both normal and non-Gaussian distributions under high-dimensional data.