D.T. Hristopulos2024-10-312024-10-3120032015-09-25D.T. Hristopulos," Spartan gibbs random field models for geostatistical applications ", J. on Sc. Comput., vol. 24 ,no. 6, pp. 2125-2162,2003. doi:10.1137/S106482750240265Xhttps://dspace.library.tuc.gr/handle/123456789/216The inverse problem of determining the spatial dependence of random fields from an experimental sample is a central issue in Geostatistics. We propose a computationally efficient approach based on Spartan Gibbs random fields. Their probability density function is determined by a small set of parameters, which can be estimated by enforcing sample-based constraints on the stochastic moments. The computational complexity of calculating the constraints increases linearly with the sample size. We investigate a specific Gibbs probability density with spatial dependence derived from generalized gradient and Laplacian operators, and we derive permissibility conditions for the model parameters.37 pagesenhttp://creativecommons.org/licenses/by/4.0/Greek mathematicsmathematics greekgreek mathematicsPeer-Reviewed Journal Publication