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Scalable Bayesian modeling for smoothing disease mapping risks in large spatial data sets using INLA
(Elsevier, 2021)
Artículo / Artikulua,
Several methods have been proposed in the spatial statistics literature to analyse big data sets in continuous domains. However, new methods for analysing high-dimensional areal data are still scarce. Here, we propose a ...
Big problems in spatio-temporal disease mapping: methods and software
(Elsevier, 2023)
Artículo / Artikulua,
Background and objective: Fitting spatio-temporal models for areal data is crucial in many fields such as cancer epidemiology. However, when data sets are very large, many issues arise. The main objective of this paper is ...