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So far, the pseudo cross-variogram is primarily used as a tool for thestructural analysis of multivariate random fields. Mainly applying recenttheoretical results on the pseudo cross-variogram, we use it as a cornerstonein the construction of valid covariance models for multivariate random fields.In particular, we extend known univariate constructions to the multivariatecase, and generalize existing multivariate models. Furthermore, we provide ageneral construction principle for conditionally negative definitematrix-valued kernels, which we use to reinterpret previous modeling proposals.

Covariance Models for Multivariate Random Fields resulting from Pseudo Cross-Variograms