Abstract

We propose a testing methodology for covariance structures in both low- and high-dimensional scenarios. The properties of the proposed tests are investigated through simulation studies, with particular emphasis on their power and bias. We also introduce asymptotic approximations based on mixtures of Gamma distributions, which are computationally efficient and straightforward to implement in practice. Numerical studies are presented to illustrate the accuracy of the proposed asymptotic approximations.