Research projects

Current third party funding

  • Statistische Modellierung von extremen Wetterereignissen in Raum und Zeit - Inferenz für zeitliche Clusterung und Homogenitätsanalyse

    (Subproject B3.3 in the joint project "Climate Change and Extreme Events - ClimXtreme II Module B - Statistics", 10/2023 - 09/2026, funded by the German Federal Ministry of Education and Research)

    Climate change influences the frequency and intensity of extreme weather events such as droughts or heavy rainfall. Under the leadership of Prof. Dr. Axel Bücher and Prof. Dr. Roland Fried (TU Dortmund University), statistical methods are to be developed and improved that will help to better assess the risk of such events.

  • Statistische Inferenz für Extremwerte von Zeitreihen basierend auf gleitenden Blockmaxima

    (Single-project (Sachbeihilfe), 10/2021 - 03/2025, funded by the German Research Foundation)

    Extreme value statistics deals with the statistical assessment of extreme and thus rare events such as heat waves, floods or stock market crashes. Under the direction of Prof. Axel Bücher, the project deals with the mathematical foundations of relevant statistical methods.

  • DigStat - Digitale Lerneinheiten in der Statistik.nrw
    2022 - 2024

    (Subproject for funding line „OERContent.nrw“, 04/2022 - 03/2024, funded by Ministry of Culture and Science NRW together with Digitalen Hochschule NRW)

    Together with experts on statistics from Bochum, Dortmund and Siegen and under the direction of Prof. Axel Bücher and JProf. Kathrin Möllenhoff from the HHU, we develop digital courses on selected statistical topics which will be made available on the ORCA.nrw platform (Open Resources Campus NRW). The target group includes not only students of mathematics, but also of natural and engineering sciences or economics.

Completed third-party funding

  • "Digitale Materialien in der Stochastik-Lehre für Präsenzveranstaltungen und Selbststudium.nrw"

    (Subproject for funding line „OERContent.nrw“, 10/2020 - 09/2022, funded by Ministry of Culture and Science NRW)

    Together with the stochastic groups in Bochum and Siegen and under the direction of Prof. Axel Bücher and Prof. Peter Kern from the HHU, online exercises are being developed for use in popular teaching platforms such as Ilias and Moodle. In addition, video tutorials and interactive applications will be used to illustrate complex stochastic facts. The target group includes not only students of mathematics, but also of natural and engineering sciences.

    Please, find further details here (MKW Website) or visit the project's website.
  • "Statistical modeling of spatio-temporal weather extremes - Inference for serial clustering and homogeneity analysis"

    (Subproject B3.3 within the BMBF-integrated project "Climate Change and Extreme Events - ClimXtreme Modul B - Statistics", 03/2020 - 02/2023, funded by Bundesministerium für Bildung und Forschung)

    Climate change has an influence on both the frequency and the intensity of extreme weather events like heat waves and heavy rain fall. Under the joint management of Prof. Dr. Axel Bücher, Prof. Dr. Roland Fried and Dr. Katharina Hees (both TU Dortmund) the project aims at the development and improvement of statistical methods which help to assess the risk of extreme weather events.

    Further details: https://www.climxtreme.net
  • "Statistical modelling of capital market dependence structure via copulas"

    (Subproject A7 within the SFB 823 "Statistical modelling of nonlinear dynamic processes", 07/2013 - 06/2021, funded by the German Science Foundation)

    The collaborative research center 823 uses and improves statistical models and methods for describing and controlling nonlinear dynamic processes arising in economics and engineering. Subproject A7, jointly managed by Axel Bücher and Prof. Gregor Weiß (Finance, until 2017) and Prof. Peter N. Posch (Finance, since 2017), extends the application and mathematical analysis of statistical models and methods for copulas for spatial and temporal dependencies in financial economics.

    Further details: www.statistik.tu-dortmund.de/sfb823.html
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