Listar UJI: Investigación por autoría "fac733f5-77c8-4ea1-8cc5-b45924c2100e"
Mostrando ítems 1-2 de 2
-
Fast Kernel Smoothing of Point Patterns on a Large Network using Two-dimensional Convolution
rakshit, suman; Davies, Tilman; Moradi, Mehdi; McSwiggan, Greg; Nair, Gopalan; Mateu, Jorge; Baddeley, Adrian Wiley (2019-06)We propose a computationally efficient and statistically principled method for kernel smoothingof point pattern data on a linear network. The point locations, and the network itself, are convolvedwith a two-dimensional ... -
Hybrids of Gibbs Point Process Models and Their Implementation
Baddeley, Adrian; Turner, Rolf; Mateu, Jorge; Bevan, Andrew Foundation for Open Access Statistics (2013)We describe a simple way to construct new statistical models for spatial point pattern data. Taking two or more existing models (finite Gibbs spatial point processes) we multiply the probability densities together and ...