build.clusters.spatial
                        Builds clusters with a given maximum size using
                        a k-means clustering.
dens.grid.maxstable     Computes the likelihood function on a grid of
                        parameters
excess.censor           Transforms data to normalized exceedances with
                        censoring
excess.l                Likelihood for vectors of exceedance with
                        censored components
margin-class            margin class
marginExp               Margin distributions
maxblocks               Computes the normalized componentwise maxima
                        with their occurrences for several blocks
maxgrid                 Identifies the coordinates of the maximum on a
                        grid
maxlik.maxstable        Maximum likelihood estimation
maxstable.l.clusters    Partition-composite likelihood for multivariate
                        max-stable distributions
mubz.copula             mu(B,z) for the copula model
mubz.lnormal            mu(B,z) for the Log-normal model
mubz.normal             mu(B,z) for the Gaussian model
plot3d.densgrid         3D visualisation of the computed values of the
                        likelihood function on a grid.
rCMS                    Simulation of vectors in the maximum domain of
                        attraction of an homogeneous clustered
                        max-stable distribution
rSchlatherExcess        Simulation of vectors in the maximum domain of
                        attraction of a spatial Schlather max-stable
                        distribution
select.mean             Selects vectors for which the mean of the
                        components is larger than a threshold
simultoccur.l           Likelihood for vectors of componentwise maxima
                        with additional information on maxima
                        occurences
spatial-class           spatial class
spatialWhittleMatern    Spatial models
