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MIA Paris

Marco Oesting

Postdoctoral Research Follow

Faculty of Geo-information Science and Earth Observation (ITC)

University of Twente

Hengelosestraat 99

PO Box 217

7500 AE Enschede

The Netherlands

+31 53 4893586



I moved to the University of Twente, Enschede, The Netherlands, where I work at the Department of Earth Observation Science.

Research Interests

  • extreme value theory and statistics
  • spatial statistics
  • simulation of stochastic processes
  • modelling of extreme events in meteorology and climatology


Work in Progress:

  • Dombry, C., Engelke, S., Oesting, M. Exact simulation of max-stable random fields.
  • Oesting, M., Bel, L., Lantuéjoul, C. Sampling from a max-stable process conditional on a homogeneous functional via Markov chain Monte Carlo techniques.


  • Dombry, C., Oesting, M., Ribatet, M. Conditional Simulation of Max-Stable Processes. Book chapter.
  • Oesting, M., Ribatet, M., Dombry, C. Simulation of Max-Stable Processes. Book Chapter.
  • Oesting, M., Schlather, M., Friederichs, P. Conditional Modelling of Extreme Wind Gusts by Bivariate Brown-Resnick Processes. Available at arXiv.
  • Oesting, M., Schlather, M. and Zhou, C. On the Normalized Spectral Representation of Max-Stable Processes on a Compact Set. Available at arXiv.
  • Ribatet, M., Dombry, C., Oesting, M. Spatial Extremes and Max-Stable Processes. Book Chapter.

Articles in Journals:

  • Oesting, M., On the distribution of a max-stable process conditional on max-linear functionals. To appear in Statistics & Probability Letters. Available at ScienceDirect.
  • Schlather, M., Malinowski, A., Menck, P.J., Oesting, M. and Strokorb, K. (2015). Analysis, simulation and prediction of multivariate random fields with package RandomFields. Journal of Statistical Software, 63(8), 1-25. Available at jstatsoft.org.
  • Engelke, S., Malinowski, A., Oesting, M. and Schlather, M. (2014). Statistical inference for max-stable processes by conditioning on extreme events. Advances in Applied Probability, 46(2), 478-495. Available at projecteuclid.org.
  • Oesting, M. and Schlather, M. (2014). Conditional Sampling for Max-Stable Processes with a Mixed Moving Maxima Representation. Extremes, 17(1), 157-192. Available at link.springer.com.
  • Oesting, M., Kabluchko, Z., und Schlather, M. (2012). Simulation of Brown-Resnick processes. Extremes, 15(1), 89-107. Available at link.springer.com.
  • Oesting, M. (2011). Book Review: Computational Statistics: An Introduction to R. Sawitzki (2009). Biometrical Journal, 53, 868.


  • Schlather, M., Malinowski, A., Oesting, M., Boecker, D., Strokorb, K., Engelke, S., Martini, J., Ballani, F., Menck, P.J., Groß, S., Ober, U., Burmeister, K., Manitz, J., Ribeiro, P., Singleton, R., Pfaff, B. and R Core Team (2015). RandomFields: Simulation and Analysis of Random Fields. R package version 3.0.60. Available at CRAN.


  • Oesting, M. (2012). Spatial Interpolation and Prediction of Gaussian and Max-Stable Processes. PhD thesis, Georg-August-Universität Göttingen. Available at Niedersächsische Staats- und Universitätsbibliothek Göttingen.
  • Oesting, M. (2009). Simulationsverfahren für Brown-Resnick-Prozesse. Diploma thesis, Georg-August-Universität Göttingen. Available at arXiv.

Former and Current Research Projects

  • McSim: Multisupport conditional simulation of max-stable processes. Applications to the local prediction of extreme climatic events (ANR)
  • WEX-MOP: Mesoscale Weather Extremes: Theory, Spatial Modeling and Prediction (Volkswagen Stiftung)