Marie-Christine Düker

Research Interests: high-dimensional time series analysis, functional data analysis, latent variable models, dimension reduction, change-point analysis, (multivariate) long-range dependence, nonstationary data and extreme value theory, applications in econometrics, neuroscience, chemistry and ecology

About

I'm an assistant professor for Mathematical Statistics and Data Science at Friedrich-Alexander University. Prior to that I was a postdoctoral associate in the Department of Statistics and Data Science at Cornell University, working with David Matteson and Gennady Samorodnitsky.

I received my PhD in Mathematics at the Faculty of Mathematics at Ruhr-University Bochum working in Herold Dehlings group and spent my PhD part-time in the Department of Statistics and Operations Research at the University of North Carolina at Chapel Hill under the supervision of Vladas Pipiras.

My current research interests include high-dimensional time series analysis, latent Gaussian count data, spectral density matrix estimation, dimension reduction, change-point analysis, functional data analysis, (multivariate) long-range dependence, nonstationary data and extreme value theory, applications in econometrics, neuroscience, chemistry and ecology.

CV

A CV can be found here.

Publications

Kim, Y, Düker, M., Fisher, Z. F., Pipiras, V.: Latent Gaussian dynamic factor modeling and forecasting for high-dimensional count time series, 2024. [arXiv].

Düker, M., Matteson, D., Tsay, R., Wilms, I.: Vector AutoRegressive Moving Average Models: A Review, 2024. [arXiv].

Düker, M., Zoubouloglou, P.: Breuer-Major Theorems for Hilbert Space-Valued Random Variables, 2024. [arXiv].

Düker, M., Pipiras, V.: Testing for common structures in high-dimensional factor models, 2024. [arXiv] [Supplement].

Baek, C., Düker, M., Pipiras, V.: Local Whittle estimation of high-dimensional long-run variance and precision matrices. The Annals of Statistics 51(6), 2386-2414, 2023. [Link] [arXiv].

Baek, C., Düker, M., Jeong, S., Lee, T.: Detection of multiple change-points in high-dimensional panel data with cross-sectional and temporal dependence. Journal of Statistical Papers, 2023. [Link] Preprint.

Xu, Y., Düker, M., Matteson, D.: Testing Simultaneous Diagonalizability. Journal of the American Statistical Association, 2023. [Link] [arXiv].

Goolsby, C., Losey, J., Xu, Y., Düker, M., Sherman Getmansky, M., Matteson, D. S., Moradi, M.: Addressing the Embeddability Problem in Transition Rate Estimation. The Journal of Physical Chemistry A, 127(27), 5745-5759, 2023. [Link] [bioRxiv].

Davidow, M., Cory, M., Che-Castaldo, J., Schafer, T., Düker, M., Corcoran, D., Matteson, D. S.: Clustering Future Scenarios Based on Predicted Range Maps. Methods in Ecology and Evolution, 2023. [Link] [arXiv].

Düker, M., Lund, R., Pipiras, V.: High-dimensional latent Gaussian count time series: Concentration results for autocovariances and applications, 2022. [arXiv].

Betken, A., Düker, M.: Higher order approximation for constructing confidence intervals in time series, 2022. [arXiv].

Schafer, T., McGranaghan, R., Getmansky Sherman, M., Feng, M., Owolabi, O., Ryan, S., Düker, M., Jauch, M., Matteson, D. S.: Risk Identification & Quantification in Complex Human-Natural Systems via Convergent Data Intensive Research. KDD Proceedings, 2021.

Düker, M., Pipiras, V., Sundararajan, R.: Cotrending: testing for common deterministic trends in varying means model. Journal of Multivariate Analysis 187, 104825, 2021. [doi] [Link] [Supplement].

Düker, M.: High-dimensional time series under long-range dependence and nonstationarity. Dissertation, 2020.

Düker, M.: Sample autocovariance operators of long-range dependent Hilbert space-valued linear processes. Preprint, 2020. [Link], 2020

Düker, M.: Limit theorems for multivariate long-range dependent processes. Stochastic Processes and their Applications 130, 5394–5425, 2020. [doi] [arXiv].

Düker, M., Pipiras, V.: Asymptotic results for multivariate local Whittle estimation with applications. 8th IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing (CAMSAP), 2019. [doi] [Supplement].

Düker, M.: Limit theorems for Hilbert space-valued linear processes under long-range dependence. Stochastic Processes and their Applications, 128(5):1439–1465, 2018. [doi].

Teaching

I have an open research assistant position for the Summer 2024. If you are interested please send me an email. I am looking for students with good statistical knowledge and programming skills.

For a Master thesis opportunity with Siemens see the following posting: Siemens.

• Winter term 2024/25, High-dimensional time series
• Winter term 2024/25, Seminar in Statistical foundations of Data Science
• Summer 2024, Introduction to Mathematical data analysis
• Summer 2024, Seminar in Statistical foundations of Data Science
• Winter term 2023/24, Special topics class in highdimensional Statistics
• Winter term 2023/24, Seminar in Statistical foundations of Data Science
• Summer term 2023, Special topics class in highdimensional Statistics

Presentations

• 7th International Conference on Econometrics and Statistics (EcoSta 2024), Beijing, 17–19th July 2024 (invited).
• 16th International Conference of the ERCIM WG on Computational and Methodological Statistics, Berlin, 16–18th December 2023 (invited).
• Seminar, Department of Mathematics, University of Athens, December 2023 (invited).
• Seminar, Department of Mathematics, EPFL, November 2023 (invited).
• NBER-NSF Time Series Conference, Montreal, September 2023.
• Joint Statistical Meetings (JSM), Toronto, August 2023 (invited).
• 6th International Conference on Econometrics and Statistics (EcoSta 2023), Waseda University Tokyo, virtual, August 2023 (invited).
• 13th Extreme Value Analysis Conference, Bocconi University Milan, June 2023 (invited).
• Conference "Women in Data Science", Friedrich-Alexander University Erlangen, virtual, April 2023 (invited).
• Seminar, Department of Statistics and Mathematics, University of Massachusetts at Amherst, March 2023 (invited).
• Conference “Adaptive and high-dimensional spatio-temporal methods for forecasting", CIRM Luminy, September 2022 (invited).
• Conference, UP-STAT 2022 Hybrid Conference, Buffalo, May 2022 (invited).
• Seminar, Department of Statistics and Data Science, Cornell University, March 2022.
• Seminar, Econometrics and Statistics, University of Chicago, Booth School of Business, virtual, March 2022 (invited).
• Seminar, Department of Statistics, University of Wisconsin Madison, virtual, February 2022 (invited).
• Seminar, Department of Statistics, University of Michigan, January 2022 (invited).
• Conference, 10th International Conference of the ERCIM WG on Computational and Methodological Statistics, virtual, 18–20th December 2021 (invited).
• Stochastics Seminar, Department Mathematics, University of Utah, October 2021.
• Conference, 10th World Congress, virtual, July 19th–23rd.
• Graduate Seminar, Department of Statistics and Operations Research, UNC Chapel Hill, September 2019.
• Conference, 40th Conference on Stochastic Processes and their Applications, Gothenburg, 11–15th of June 2018.
• 13th German Probability and Statistics Days, Freiburg, 27th February - 02nd March 2018.
• Conference, 10th International Conference of the ERCIM WG on Computational and Methodological Statistics, London, 16-18th December 2017.
• Graduate Seminar, Department of Statistics and Operations Research, TU Dortmund, November 2017.
• Conference, 31st European Meeting of Statisticians, Helsinki, 24-28th July 2017.

Contact

Friedrich-Alexander University
Department of Statistics and Data Science
Tech campus
Cauerstr. 11
Erlangen, Germany

E-Mail: marie.dueker@fau.de