A new class of non-Gaussian multivariate random fields is formulated using systems of stochastic partial differential equations with additive type-G noise. We consider four increasingly

Covariance tapering is a popular approach for reducing the computational cost of spatial prediction and parameter estimation for Gaussian process models. However, tapering can have