A joint covariance construction for Gaussian priors preserves given marginals, permits arbitrary cross-correlations via contractions, and supports inference on the correlation structure itself.
Analysis of boundary effects on PDE-based sampling of Whittle–Mat´ ern random fields.SIAM/ASA Journal on Uncertainty Quantification, 7(3):948–974
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Beyond Independence: on Jointly Normal Priors in Bayesian Inversion
A joint covariance construction for Gaussian priors preserves given marginals, permits arbitrary cross-correlations via contractions, and supports inference on the correlation structure itself.