Random Fields Based on Local Interactions

In this chapter we look at random fields from a perspective that is common in statistical physics but not so much in spatial data analysis. This perspective is useful, because it can lead to computationally efficient methods for spatial prediction, while it is also related with Markovian random fields. In addition, it enables the calculation of new forms of covariance functions and provides a link with stochastic partial differential equations.