Modelling Spatial Extremes


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Documentation for package ‘SpatialExtremes’ version 1.0-0

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anova Anova Tables
condmap Produces a conditional 2D map from a fitted max-stable process
covariance Defines and computes covariance functions
cv Estimates the penalty coefficient from the cross-validation criterion
distance Computes distance between pairs of locations
extcoeff Plots the extremal coefficient
fitcovariance Estimates the covariance function for the Schlather's model
fitcovmat Estimates the covariance matrix for the Smith's model
fitextcoeff Non parametric estimators of the extremal coefficient function
fitmaxstab Fits a max-stable process to data
frech2gev Transforms GEV data to unit Frechet ones and vice versa
gcv Estimates the penalty coefficient from the generalized cross-validation criterion
gev2frech Transforms GEV data to unit Frechet ones and vice versa
gevmle Fits univariate extreme value distributions to data
gpdmle Fits univariate extreme value distributions to data
logLik Extracts Log-Likelihood
madogram Computes madograms
map Produces a 2D map from a fitted max-stable process
modeldef Define a model for the spatial behaviour of the GEV parameters
predict.maxstab Prediction of the max-stable marginal parameters
predict.pspline Prediction of smoothing spline with radial basis functions
print.maxstab Printing objects of class “maxstab”
print.pspline Printing objects of class “pspline”
profile Method for profiling fitted max-stable objects
profile2d Method for profiling (in 2d) fitted max-stable objects
rb Creates a model using penalized smoothing splines
rbpspline Fits a penalized spline with radial basis functions to data
SpatialExtremes Analysis of Spatial Extremes
TIC Takeuchi's information criterion