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Spatial data modeling by means of Gibbs Markov random fields based on a generalized planar rotator model
[article]
2022
arXiv
pre-print
We introduce a Gibbs Markov random field for spatial data on Cartesian grids which is based on the generalized planar rotator (GPR) model. The GPR model generalizes the recently proposed modified planar rotator (MPR) model by including in the Hamiltonian additional terms that better capture realistic features of spatial data, such as smoothness, non-Gaussianity, and geometric anisotropy. In particular, the GPR model includes up to infinite number of higher-order harmonics with exponentially
arXiv:2201.02537v1
fatcat:d2glhovcdvgrlmvisysvkmnel4