摘要：We survey the current practice of analyzing spatial extreme data, which lies at the intersection
of extreme value theory and geostatistics. Characterizations of multivariate
max-stable distributions typically assume specific univariate marginal distributions,
and their statistical applications generally require capturing the tail behavior of the
margins and describing the tail dependence among the components. We review current
methodology for spatial extremes analysis, discuss the extension of the finite-dimensional
extremes framework to spatial processes, review spatial dependence metrics
for extremes, survey current modeling practice for the task of modeling marginal
distributions, and then examine max-stable process models and copula approaches
for modeling residual spatial dependence after accounting for marginal effects.
关键词：copula; extremal coefficient; hierarchical model; madogram; max-stable process; multi-
variate extreme value distribution
