3 papers
stat.CO2025
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)),…
stat.CO2024
Efficient estimation for a smoothing thin plate spline in a two-dimensional space
Joaquin Cavieres, Michael Karkulik
Using a deterministic framework allows us to estimate a function with the purpose of interpolating data in spatial statistics. Radial basis functions are commonly used for scattere…