This image shows Marco Oesting

Marco Oesting

Jun.-Prof. Dr. rer. nat.

SimTech Tenure-Track Professorship for "Computational Statistics"


Allmandring 5b
70569 Stuttgart
Room: 2.34

Office Hours

Please contact me by E-Mail


  • Extreme value theory and statistics
  • Spatial Statistics
  • Simulation of stochastic processes and random fields
  • Statistical modelling of extreme events in climate and environmental sciences

More information on research topics and current projects can be found here.

WS 2020/21
Lineare Strukturen (SimTech B.Sc.)
Stochastic Simulation I (Mathematics M.Sc. & SimTech M.Sc.)

10/2005 - 09/2009 

Studies in Mathematics, University of Göttingen


Diploma in Mathematics with Prof. Dr. M. Schlather, University of Göttingen

10/2009 - 05/2012 

PhD student at the Institute for Mathematical Stochastics, University of Göttingen, within the DFG Research Training
Group 1023 "Identification in Mathematical Models: Synergy of Stochastic and Numerical Methods"


PhD in Mathematics with Prof. Dr. M. Schlather, University of Göttingen

06/2012 - 12/2013 

Research Assistant at the Institute of Mathematics, University of Mannheim, within the project WEX-MOP
(Mesoscale Weather Extremes: Theory, Spatial Modeling and Prediction; Volkswagen Stiftung)

12/2013 - 12/2014 


Postdoctoral Researcher at the Division of Applied Mathematics and Informatics (MIA), INRA/AgroParisTech, within
the project McSim (Multisupport conditional simulation of max-stable processes. Applications to the local prediction
of extreme climatic events; Agence Nationale de la Recherche)

01/2015 - 09/2015 

Postdoctoral Researcher at the Department of Earth Observation Science, Faculty of Geo-Information Science and
Earth Observation (ITC), University of Twente

10/2015 - 03/2018 and 10/2018 - 07/2020

Akademischer Rat auf Zeit at the Department of Mathematics, University of Siegen

04/2018 - 09/2018

Interim Professorship of Stochastics at the Faculty of Mathematics and Economics, University of Ulm


Habilitation in Mathematics; Department of Mathematics, University of Siegen

since 08/2020

Tenure-Track Professorship for Computational Statistics at the Stuttgart Center for Simulation Science (SC SimTech) and the Institute for Stochastics and Applications, University of Stuttgart


  • M. Oesting & O. Wintenberger. Estmiation of the Spectral Measure from Convex Combinations of Regularly Varying Random Vectors. Available at arXiv.
  • M. Oesting & P. Naveau. Spatial Modeling of Heavy Precipitation by Coupling Weather Station Recordings and Ensemble Forecasts with Max-Stable Processes. Available at arXiv.
  • M. Oesting & K. Strokorb. A comparative tour through the simulation algorithms for max-stable processes. Available at arXiv.
  • C. Dombry, S. Engelke & M. Oesting. Asymptotic Properties of the Maximum Likelihood Estimator for Multivariate Extreme Value Distributions. Available at arXiv.

Articles in Refereed Journals

  • V. Makogin, M. Oesting, A. Rapp & E. Spodarev (2020+). Long Range Dependence for Stable Random Processes. Accepted for publication in Journal of Time Series Analysis. Available at arXiv.
  • M. Oesting & A. Schnurr (2020+). Ordinal Patterns in Clusters of Subsequent Extremes of Regularly Varying Time Series. Accepted for publication in Extremes. Available at
  • M. Oesting, M. Schlather & C. Schillings (2019). Sampling Sup-Normalized Spectral Functions for Brown-Resnick Processes. Stat, 8(1), e228. Available at
  • S. Engelke, R. de Fondeville & M. Oesting (2019). Extremal Behavior of Aggregated Data with an Application to Downscaling. Biometrika, 106(1), 127-144. Available at
  • M. Oesting & K. Strokorb (2018). Efficient simulation of Brown-Resnick processes based on variance reduction of Gaussian processes. Advances in Applied Probability, 50(4), 1155-1175. Available at
  • M. Oesting, L. Bel & C. Lantuéjoul (2018). Sampling from a Max-Stable Process Conditional on a Homogeneous Functional with an Application for Downscaling Climate Data. Scandinavian Journal of Statistics, 45(2), 382-404. Available at
  • M. Oesting (2018). Equivalent Representations of Max-Stable Processes via lp Norms. Journal of Applied Probability, 55(1), 54-68. Available at
  • M. Oesting & A. Stein (2018). Spatial Modeling of Drought Events Using Max-Stable Processes. Stochastic Environmental Research and Risk Assessment, 32(1), 63-81. Available at
  • M. Oesting, M. Schlather & C. Zhou (2018). Exact and Fast Simulation of Max-Stable Processes on a Compact Set Using the Normalized Spectral Representation. Bernoulli, 24(2), 1497-1530. Available at
  • C. Dombry, S. Engelke & M. Oesting (2017). Bayesian Inference for Multivariate Extreme Value Distributions. Electronic Journal of Statistics, 11(2), 4813-4844. Available at
  • M. Oesting, M. Schlather & P. Friederichs (2017). Statistical Post-Processing of Forecasts for Extremes Using Bivariate Brown-Resnick Processes with an Application to Wind Gusts. Extremes, 20(2), 309-332. Available at
  • C. Dombry, S. Engelke & M. Oesting (2016). Exact simulation of max-stable processes. Biometrika, 103(2), 303-317. Available at
  • M. Schlather, A. Malinowski, P.J. Menck, M. Oesting & K. Strokorb (2015). Analysis, simulation and prediction of multivariate random fields with package RandomFields. Journal of Statistical Software, 63(8), 1-25. Available at
  • M. Oesting (2015). On the distribution of a max-stable process conditional on max-linear functionals. Statistics & Probability Letters, 100, 158-163. Available at ScienceDirect.
  • S. Engelke, A. Malinowski, M. Oesting & M. Schlather (2014). Statistical inference for max-stable processes by conditioning on extreme events. Advances in Applied Probability, 46(2), 478-495. Available at
  • M. Oesting & M. Schlather (2014). Conditional Sampling for Max-Stable Processes with a Mixed Moving Maxima Representation. Extremes, 17(1), 157-192. Available at
  • M. Oesting, Z. Kabluchko & M. Schlather (2012). Simulation of Brown-Resnick processes. Extremes, 15(1), 89-107. Available at

 Book Chapters

  • C. Dombry, M. Oesting & M. Ribatet (2016). Conditional Simulation of Max-Stable Processes. In Dey, D.K., Yan, J. (Ed.), Extreme Value Modeling and Risk Analysis: Methods and Applications (pp. 215-238), Boca Raton: CRC Press.
  • M. Oesting, M. Ribatet & C. Dombry (2016). Simulation of Max-Stable Processes. In Dey, D.K., Yan, J. (Ed.), Extreme Value Modeling and Risk Analysis: Methods and Applications (pp. 195-214), Boca Raton: CRC Press.
  • M. Ribatet, C. Dombry & M. Oesting (2016). Spatial Extremes and Max-Stable Processes. In Dey, D.K., Yan, J. (Ed.), Extreme Value Modeling and Risk Analysis: Methods and Applications (pp. 179-194), Boca Raton: CRC Press.

Book Reviews

  • M. Oesting (2011). Book Review: Computational Statistics: An Introduction to R. Sawitzki (2009). Biometrical Journal, 53, 868.


  • M. Schlather, A. Malinowski, M. Oesting, D. Boecker, K. Strokorb, S. Engelke, J. Martini, F. Ballani, O. Moreva, J. Aue, P.J. Menck, S. Groß, U. Ober, P. Ribeiro, R. Singleton, B. Pfaff and R Core Team (2019). RandomFields: Simulation and Analysis of Random Fields. R package version 3.3.1. Available at CRAN.


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

I am a member of the organizing team of the 'One World Extremes Seminar'. You can find more information under

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