A complex cross-spectral distribution model using Normal Variance Mean Mixtures

We propose a model for the density of cross-spectral coefficients using normal variance mean mixtures. We show that this model density generalizes the corresponding marginal density of the complex Wishart distribution for the cross-spectral density. The maximum likelihood estimate of parameters in the distribution is derived, and examples are given from alpha brain wave sources in separated EEG data.