If we dispose of block, e.g., annual, maxima observed at locations , univariate extreme value arguments suggests that these block maxima might be modelled by a GEV distribution. The key idea of the latent process approach is to assume that the GEV parameters vary smoothly over space according to a stochastic process . The SpatialExtremes package use Gaussian processes for this and assume that the Gaussian processes related to each GEV parameter are mutually independent. For instance we take

Then conditional on the values of the three Gaussian processes at the weather stations, the block maxima are assumed to follow a GEV distribution