5 papers · 1 filter
Distributed and recursive Bayesian inference for Big Data and complex spatio-temporal models
Mario Figueira, David Conesa, Antonio López-Quílez +1
The rapid growth of massive and complex datasets in fields such as econometrics, environmental sciences, risk management, and public policy has reshaped statistical modeling while…
INLA-RF: A Hybrid Modeling Strategy for Spatio-Temporal Environmental Data
Mario Figueira, Michela Cameletti, Luca Patelli
Environmental processes often exhibit complex, non-linear patterns and discontinuities across space and time, posing significant challenges for traditional geostatistical modeling…
Integrating Expert Knowledge and Recursive Bayesian Inference: A Framework for Spatial and Spatio-Temporal Data Challenges
Mario Figueira, David Conesa, Antonio López-Quílez +1
Integrating heterogeneous data sources and expert knowledge is essential for overcoming data scarcity and enhancing estimation accuracy. Two main frameworks naturally arise to perf…
Unveiling land use dynamics: Insights from a hierarchical Bayesian spatio-temporal modelling of Compositional Data
Mario Figueira, Carmen Guarner, David Conesa +2
Changes in land use patterns have significant environmental and socioeconomic impacts, making it crucial for policymakers to understand their causes and consequences. This study, p…
A computationally efficient procedure for combining ecological datasets by means of sequential consensus inference
Mario Figueira, David Conesa, Antonio López-Quílez +1
Combining data has become an indispensable tool for managing the current diversity and abundance of data. But, as data complexity and data volume swell, the computational demands o…