2 citations · 2 across the 4 of their papers we have counts for
4 papers
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)),…
Spatial Latent Gaussian Modelling with Change of Support
Erick A. Chacón-Montalván, Peter M. Atkinson, Christopher Nemeth +2
Spatial data are often derived from multiple sources (e.g. satellites, in-situ sensors, survey samples) with different supports, but associated with the same properties of a spatia…
On adaptive kernel intensity estimation on linear networks
Jonatan A. González, Paula Moraga
In the analysis of spatial point patterns on linear networks, a critical statistical objective is estimating the first-order intensity function, representing the expected number of…
An adaptive kernel estimator for the intensity function of spatio-temporal point processes
Jonatan A. González, Paula Moraga
In spatio-temporal point pattern analysis, one of the main statistical objectives is to estimate the first-order intensity function, i.e., the expected number of points per unit ar…