, Volume 17, Issue 1, pp 157–192 | Cite as

Conditional sampling for max-stable processes with a mixed moving maxima representation

  • Marco Oesting
  • Martin Schlather


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.


Conditional sampling Extremes Max-stable process Mixed moving maxima Poisson point process 

AMS 2000 Subject Classifications

60G70 60D05 


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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  1. 1.Institute of MathematicsUniversity of MannheimMannheimGermany

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