Contact
Allmandring 5b
70569 Stuttgart
Germany
Room: 1.33
Office Hours
Please contact me by E-Mail
Subject
- 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.
Preprints
- M. Oesting & A. Rapp. Long Memory of Max-Stable Time Series as Phase Transition: Asymptotic Behaviour of Tail Dependence Estimators. Available at arXiv.
- J. Lederer & M. Oesting. Extremes in high dimensions: Methods and scalable algorithms. Available at arXiv.
- C. Forster & M. Oesting. Non-stationary max-stable models with an application to heavy rainfall data. Available at arXiv.
- M. Oesting & R. Huser. Patterns in Spatio-Temporal Extremes. Available at arXiv.
- M. Oesting, A. Rapp & E. Spodarev. Detection of Long Range Dependence in the Time Domain for (In) Finite-Variance Time Series. Available at arXiv.
- J. Legrand, P. Naveau & M. Oesting. Evaluation of binary classifiers for asymptotically dependent and independent extremes. Available at arXiv.
- M. Oesting & O. Wintenberger. Estimation of the Spectral Measure from Convex Combinations of Regularly Varying Random Vectors. Available at HAL.
- M. Oesting & P. Naveau. Spatial Modeling of Heavy Precipitation by Coupling Weather Station Recordings and Ensemble Forecasts with 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
- C. Bernard, A. Müller & M. Oesting (2023+). Lp-norm spherical copulas. To appear in Journal of Multivariate Analysis. Preprint available at arXiv.
- O.E. Jurado, M. Oesting, H.W. Rust (2023). Implications of modeling seasonal differences in the extremal dependence of rainfall maxima. Stochastic Environmental Research and Risk Assessment, 37, 1963-1981. Available at link.springer.com.
- V. Wagner, B. Castellaz, M. Oesting & N. Radde (2022). Quasi-Entropy Closure: A Fast and Reliable Approach to Close the Moment Equations of the Chemical Master Equation. Bioinformatics, 38(18), 4352–4359. Available at academic.oup.com.
- M. Oesting & K. Strokorb (2022). A comparative tour through the simulation algorithms for max-stable processes. Statistical Science, 37(1), 42-63. Available at projecteuclid.org.
- V. Makogin, M. Oesting, A. Rapp & E. Spodarev (2021). Long Range Dependence for Stable Random Processes. Journal of Time Series Analysis, 42(2), 161-185. Available onlinelibrary.wiley.com.
- M. Oesting & A. Schnurr (2020). Ordinal Patterns in Clusters of Subsequent Extremes of Regularly Varying Time Series. Extremes, 23, 521-545. Available at link.springer.com.
- M. Oesting, M. Schlather & C. Schillings (2019). Sampling Sup-Normalized Spectral Functions for Brown-Resnick Processes. Stat, 8(1), e228. Available at onlinelibrary.wiley.com.
- 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 academic.oup.com.
- 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 cambridge.org.
- 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 onlinelibrary.wiley.com.
- M. Oesting (2018). Equivalent Representations of Max-Stable Processes via lp Norms. Journal of Applied Probability, 55(1), 54-68. Available at cambridge.org.
- 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 link.springer.com.
- 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 projecteuclid.org.
- C. Dombry, S. Engelke & M. Oesting (2017). Bayesian Inference for Multivariate Extreme Value Distributions. Electronic Journal of Statistics, 11(2), 4813-4844. Available at projecteuclid.org.
- 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 link.springer.com.
- C. Dombry, S. Engelke & M. Oesting (2016). Exact simulation of max-stable processes. Biometrika, 103(2), 303-317. Available at oxfordjournals.org.
- 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 jstatsoft.org.
- 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 projecteuclid.org.
- M. Oesting & M. Schlather (2014). Conditional Sampling for Max-Stable Processes with a Mixed Moving Maxima Representation. Extremes, 17(1), 157-192. Available at link.springer.com.
- M. Oesting, Z. Kabluchko & M. Schlather (2012). Simulation of Brown-Resnick processes. Extremes, 15(1), 89-107. Available at link.springer.com.
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.
Software
- 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.
Theses
- M. Oesting (2020). Analysis and simulation of multivariate and spatial extremes. Habilitation thesis, Universität Siegen. Available at OPUS Siegen.
- 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.
Winter Term 2023/2024
Stochastic Simulation I (Mathematik M.Sc. & SimTech M.Sc.)
Stochastik und Angewandte Mathematik für das Lehramt (Lehramt Mathematik)
Summer Term 2023
Stochastische Prozesse (Mathematik B.Sc.)
Winter Term 2022/23
Mathematische Statistik (Mathematik B.Sc.)
Summer Term 2022
Maß- und Wahrscheinlichkeitstheorie (Mathematik B.Sc.)
Winter Term 2021/22
Stochastic Simulation I (Mathematik M.Sc. & SimTech M.Sc.)
Summer Term 2021
Stochastic Simulation II (Mathematik M.Sc. & SimTech M.Sc.)
Winter Term 2020/21
Lineare Strukturen (SimTech B.Sc.)
Stochastic Simulation I (Mathematik M.Sc. & SimTech M.Sc.)
Curriculum Vitae
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10/2005 - 09/2009 |
Studies in Mathematics, University of Göttingen |
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09/2009 |
Diploma in Mathematics with Prof. Dr. M. Schlather, University of Göttingen |
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10/2009 - 05/2012 |
PhD student at the Institute for Mathematical Stochastics, University of Göttingen, within the DFG Research Training |
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05/2012 |
PhD in Mathematics with Prof. Dr. M. Schlather, University of Göttingen |
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06/2012 - 12/2013 |
Research Assistant at the Institute of Mathematics, University of Mannheim, within the project WEX-MOP |
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12/2013 - 12/2014 |
Postdoctoral Researcher at the Division of Applied Mathematics and Informatics (MIA), INRA/AgroParisTech, within |
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01/2015 - 09/2015 |
Postdoctoral Researcher at the Department of Earth Observation Science, Faculty of Geo-Information Science and |
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10/2015 - 03/2018 and 10/2018 - 07/2020 |
Akademischer Rat auf Zeit at the Department of Mathematics, University of Siegen |
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04/2018 - 09/2018 |
Interim Professorship of Stochastics at the Faculty of Mathematics and Economics, University of Ulm |
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08/2020 |
Habilitation in Mathematics; Department of Mathematics, University of Siegen |
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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 |
I am the contact person for the lecture series "Mathe Macht! Mathematik in der Praxis", where companies that use mathemaYou can find more information under https://www.f08.uni-stuttgart.de/mathematik/studierende/mathemacht/
From 2020 to 2023, I was a member of the organizing team of the 'One World Extremes Seminar'. You can find more information under https://sites.google.com/view/ow-extremes/home
Jun.-Prof. Oesting, is there a connection between heat waves, storms and floods and mathematics?