  In environmental applications of extreme value statistics, the underlying
stochastic process is often modeled either as a max-stable process in
continuous time/space or as a process in the domain of attraction of such a
max-stable process. In practice, however, the processes are typically only
observed at discrete points and one has to resort to interpolation to fill in
the gaps. We discuss the influence of such an interpolation on estimators of
marginal parameters as well as estimators of the exponent measure. In
particular, natural conditions on the fineness of the observational scheme are
developed which ensure that asymptotically the interpolated estimators behave
in the same way as the estimators which use fully observed continuous
processes.
