Prior Models

This chapter presents stationary versions of the Gaussian, Poisson and Markov random field models as prior models for spatial continuous, event and mosaic variables, respectively. For each of these prior models, detailed discussions of their parametrisations and characteristics are presented. We discuss topics specifically related to each prior model and present prior models based on hierarchical versions of the random fields under study. The running examples are continued.