3 papers
stat.ME2025
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…
stat.ME2025
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…
stat.ME2025
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…