A LASSO-penalized framework induces sparsity in the Cholesky factor of multivariate Matérn correlation matrices, allowing automatic detection of uncorrelated variable pairs while preserving positive semidefiniteness for feasible estimation in high-dimensional spatial fields.
SinceU N(θ) andK(θ, θ 0) (defined in Equation (17)) are compositions of continuous functions, they are themselves continuous
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Regularized estimation for highly multivariate spatial Gaussian random fields
A LASSO-penalized framework induces sparsity in the Cholesky factor of multivariate Matérn correlation matrices, allowing automatic detection of uncorrelated variable pairs while preserving positive semidefiniteness for feasible estimation in high-dimensional spatial fields.