Simultaneous test of the mean vectors and covariance matrices for
high-dimensional data using RMT
Simultaneous test of the mean vectors and covariance matrices for
high-dimensional data using RMT
In this paper, we propose a new modified likelihood ratio test (LRT) for simultaneously testing mean vectors and covariance matrices of two-sample populations in high-dimensional settings. By employing tools from Random Matrix Theory (RMT), we derive the limiting null distribution of the modified LRT for generally distributed populations. Furthermore, we …