Abstract
This paper deals with the question of conditional sampling and prediction for the class of stationary max-stable processes which allow for a mixed moving maxima representation. We develop an exact procedure for conditional sampling using the Poisson point process structure of such processes. For explicit calculations we restrict ourselves to the one-dimensional case and use a finite number of shape functions satisfying some regularity conditions. For more general shape functions approximation techniques are presented. Our algorithm is applied to the Smith process and the Brown-Resnick process. Finally, we compare our computational results to other approaches. Here, the algorithm for Gaussian processes with transformed marginals turns out to be surprisingly competitive.
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Oesting, M., Schlather, M. Conditional sampling for max-stable processes with a mixed moving maxima representation. Extremes 17, 157–192 (2014). https://doi.org/10.1007/s10687-013-0178-1
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DOI: https://doi.org/10.1007/s10687-013-0178-1