作者：Dunson, David; Wood, Simon
作者：Bolin, David; Wallin, Jonas
作者单位：King Abdullah University of Science & Technology; University of Gothenburg; Lund University
摘要：For many applications with multivariate data, random-field models capturing departures from Gaussianity within realizations are appropriate. For this reason, we formulate a new class of multivariate non-Gaussian models based on systems of stochastic partial differential equations with additive type G noise whose marginal covariance functions are of Matern type. We consider four increasingly flexible constructions of the noise, where the first two are similar to existing copula-based models. In...
