Research Associate
Helmut-Schmidt-University
University of the Federal Armed Forces Hamburg
Holstenhofweg 85
22043 Hamburg
Room: H1, 1370
Phone: +49 40 6541-2885
Fax: +49 40 6541-2023
E-Mail: [email protected]
Education
- 11/2014 – 12/2020: Doctoral studies, Mathematics, Technische Universität Braunschweig
- 10/2012 – 11/2014: Master of Science, Mathematics in Finance and Industry, Technische Universität Braunschweig
- 09/2013 – 01/2014: M2 Probabilités et Finance, Université Pierre et Marie Curie and École polytechnique, Paris
- 10/2009 – 10/2012: Bachelor of Science, Mathematics in Finance and Industry, Technische Universität Braunschweig
- 06/2009: Abitur Ratsgymnasium Stadthagen
Career
- 11/2014 – 03/2021: Research assistant, Technische Universität Braunschweig
Publications
- Beering, C. (2024). Bridge Monitoring and Independence Testing for Locally Stationary Processes. Joint Statistical Meeting (JSM), Portland. https://doi.org/10.5281/zenodo.13356531.
- Beering, C. (2024). Bridge Monitoring with the Help of Local Distance Correlation. e-Journal of Nondestructive Testing, DOI: 10.58286/29599.
- Rentala, V. K., Kanzler, D., Kessler, S., Jaelani, Y., Knoth, S., Beering, C. (2024). POD methodologies for SHM application in civil engineering. e-Journal of Nondestructive Testing, DOI: 10.58286/29824.
- Beering, C., Leucht, A. (2023). A bootstrap functional central limit theorem for time-varying linear processes. Journal of Nonparametric Statistics, DOI: 10.1080/10485252.2023.2284896.
- Beering, C. (2021). A Functional Central Limit Theorem and its Bootstrap Analogue for Locally Stationary Processes with Application to Independence Testing. Dissertation. Technische Universität Braunschweig (view online).
- Jentsch, C., Leucht, A., Meyer, M., Beering, C. (2020). Empirical characteristic function-based estimation and distance correlation for locally stationary processes. Journal of Time Series Analysis 41, 110-133.
Teaching
- Spring 2024: Time Series Analysis
- Fall 2023: Quantitative Methods IV
- Winter 2023: Stochastic Processes
- Fall 2022: Advanced Statistics
- Winter 2022: Quantitative Methods II
- Fall 2021: Quantitative Methods IV
Letzte Änderung: 12. December 2024