4 papers · 1 filter
Gibbs sampling for Bayesian P-splines
Oswaldo Gressani, Paul H. C. Eilers
P-splines provide a flexible setting for modeling nonlinear model components based on a discretized penalty structure with a relatively simple computational backbone. Under a Bayes…
A Time-Series Model for Areal Data Using Area-Specific Gaussian Processes with Spatially Correlated Hyperparameters
Alejandro Rozo Posada, Oswaldo Gressani, Christel Faes +4
In many applied settings, areal data are observed repeatedly over long time periods, as commonly occurs in infectious disease surveillance and environmental or demographic monitori…
Distributed lag non-linear models with Laplacian-P-splines for analysis of spatially structured time series
Sara Rutten, Bryan Sumalinab, Oswaldo Gressani +4
Distributed lag non-linear models (DLNM) have gained popularity for modeling nonlinear lagged relationships between exposures and outcomes. When applied to spatially referenced dat…
A Low-Rank Bayesian Approach for Geoadditive Modeling
Bryan Sumalinab, Oswaldo Gressani, Niel Hens +1
Kriging is an established methodology for predicting spatial data in geostatistics. Current kriging techniques can handle linear dependencies on spatially referenced covariates. Al…