Now showing items 1-2 of 2

    • closedAccess   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 ...
    • openAccess   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 ...