4 papers
Extensions in Semiparametric Geostatistical Models
MaÃra Soalheiro, Marcos Oliveira Prates, Victor Hugo Lachos +1
In spatial statistics, the incorrect selection of an appropriate covariance function may lead to inference errors and confidence underestimation. Motivated by such restrictions, we…
Spatial Confounding: A review of concepts, challenges, and current approaches
Isaque Vieira Machado Pim, Luiz Max Fagundes de Carvalho, Marcos Oliveira Prates
Spatial confounding is a persistent challenge in spatial statistics, influencing the validity of statistical inference in models that analyze spatially-structured data. The concept…
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…
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…