Published
Songklanakarin Journal of Science and Technology
A Covariance matrix test for High-dimensional Data,
Abstract
For the multivariate normally distributed data with the dimension larger than or equal to the number of observations, or the sample size, called high-dimensional normal data, we proposed a test for testing the null hypothesis that the covariance matrix of a normal population is proportional to a given matrix on some conditions when the dimension goes to infinity. We showed that this test statistic is consistent. The asymptotic null and non-null distribution of the test statistic is also given. The performance of the proposed test is evaluated via simulation study and its application.
(2016). A Covariance matrix test for High-dimensional Data,. Songklanakarin Journal of Science and Technology, 38(5), 521-535.