2 papers
stat.CO2026
regTPS-KLE: A Novel Approach To Approximate A Gaussian Random Field for Bayesian Spatial Modeling
Joaquin Cavieres, Sebastian Krumscheid
Gaussian random field is a ubiquitous model for spatial phenomena in diverse scientific disciplines. Its approximation is often crucial for computational feasibility in simulation,…
stat.ME2024
Why not a thin plate spline for spatial models? A comparative study using Bayesian inference
Joaquin Cavieres, Paula Moraga, Cole C. Monnahan
Spatial modelling often uses Gaussian random fields to capture the stochastic nature of studied phenomena. However, this approach incurs significant computational burdens (O(n3)),…