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stat.ME2026
Kriging Beyond Gaussianity: Fixed-Domain Asymptotic Optimality
Moreno Bevilacqua, Hector Araya
Under squared-error loss, the optimal predictor of a non-Gaussian random field is its conditional mean, which may be difficult to compute. We consider a broad class of non-Gaussian…
stat.ME2026
Fast Stochastic Nearest Neighbor Pairwise Composite Likelihood for Massive Spatial Datasets
Moreno Bevilacqua, Francisco Cuevas-Pacheco, Christian Caamaño-Carrillo
Weighted pairwise composite likelihoods based on nearest-neighbor (NN) pairs provide a scalable alternative to full likelihood inference for spatial random fields, but can remain e…
stat.ME2025
Parsimonious Compactly Supported Covariance Models in the Gauss Hypergeometric Class: Identifiability, Reparameterizations, and Asymptotic Properties
Moreno Bevilacqua, Christian Caamaño-Carrillo, Tarik Faouzi +1
We study covariance functions in the Gauss hypergeometric () class, a flexible family that encompasses the Generalized Wendland () and Matérn ($\mathcal…