32 citations · 41 across the 18 of their papers we have counts for
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stat.ME2022
Statistical Inferences and Predictions for Areal Data and Spatial Data Fusion with Hausdorff--Gaussian Processes
Lucas da Cunha Godoy, Marcos Oliveira Prates, Jun Yan
Accurate modeling of spatial dependence is pivotal in analyzing spatial data, influencing parameter estimation and predictions. The spatial structure of the data significantly impa…
stat.ME2022★ 1 cited
The Poisson-Gaussian Mixture Process: A Flexible and Robust Approach for Non-Gaussian Geostatistical Modeling
F. B. Gonçalves, M. O. Prates, G. A. S. Aguilar
This paper introduces a novel family of geostatistical models designed to capture complex features beyond the reach of traditional Gaussian processes. The proposed family, termed t…