21 citations · 42 across the 7 of their papers we have counts for
7 papers · 1 filter
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…
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…
Penalty parameter selection and asymmetry corrections to Laplace approximations in Bayesian P-splines models
Philippe Lambert, Oswaldo Gressani
Laplacian-P-splines (LPS) associate the P-splines smoother and the Laplace approximation in a unifying framework for fast and flexible inference under the Bayesian paradigm. Gaussi…
Laplacian-P-splines for Bayesian inference in the mixture cure model
Oswaldo Gressani, Christel Faes, Niel Hens
The mixture cure model for analyzing survival data is characterized by the assumption that the population under study is divided into a group of subjects who will experience the ev…
Laplace approximation for fast Bayesian inference in generalized additive models based on penalized regression splines
Oswaldo Gressani, Philippe Lambert
Generalized additive models (GAMs) are a well-established statistical tool for modeling complex nonlinear relationships between covariates and a response assumed to have a conditio…