A. Betken (Annika)

Assistant Professor
EEMCS-AM-MOR
Zilverling 2047
a.betken@utwente.nl
Business card

My personal webpage:  https://annikabetken.github.io

Expertise

  • Mathematics

    • Long Range
    • Stochastic Volatility
    • Range Dependence
    • Simulation Study
    • Test Statistic
    • Change Point Analysis
    • Tail Index
    • Tail Parameter

Organisations

Publications

2024
Test for independence of long-range dependent time series using distance covariance. ArXiv.org. Betken, A. & Dehling, H.https://doi.org/10.48550/arXiv.2107.03041Class Probability Matching with Calibrated Networks for Label Shift AdaptationIn Class Probability Matching with Calibrated Networks for Label Shift Adaptation. Betken, A., Wen, H. & Hang, H.Higher-order approximation for constructing confidence intervals in time series (Submitted). Betken, A. & Düker, M.-C.Depth Patterns (Unpublished). Betken, A. & Schnurr, A.
2023
Change-point tests for the tail parameter of Long Memory Stochastic Volatility time series, 2017-2039. Betken, A., Giraudo, D. & Kulik, R.https://doi.org/10.5705/ss.202020.0265Class Probability Matching Using Kernel Methods for Label Shift Adaptation (Unpublished). Betken, A., Hang, H. & Wen, H.
2022
Rank-based change-point analysis for long-range dependent time series, 2209-2233. Betken, A. & Wendler, M.https://doi.org/10.3150/21-BEJ1416
2021
Block Bootstrapping the Empirical Distance Covariance. ArXiv.org. Betken, A., Dehling, H. & Kroll, M.https://arxiv.org/abs/2112.14091Ordinal pattern dependence as a multivariate dependence measure, Article 104798. Betken, A., Dehling, H., Nüßgen, I. & Schnurr, A.https://doi.org/10.1016/j.jmva.2021.104798
2020
Change-point tests for the tail parameter of Long Memory Stochastic Volatility time series. ArXiv.org. Betken, A., Giraudo, D. & Kulik, R.https://arxiv.org/abs/2006.02667Rank-based change-point analysis for long-range dependent time series. ArXiv.org. Betken, A. & Wendler, M.https://arxiv.org/abs/2004.06574Ordinal patterns in long-range dependent time series. Betken, A., Buchsteiner, J., Dehling, H., Münker, I., Schnurr, A. & Woerner, J. H. C.https://doi.org/10.1111/sjos.12478
2019
Testing for Change in Long-Memory Stochastic Volatility Time Series, 707-738. Betken, A. & Kulik, R.https://doi.org/10.1111/jtsa.12449

Other contributions

Betken, A., Dehling, H., Münker, I., Schnurr, A. (2020): Ordinal pattern dependence as a multivariate dependence measure. Preprint, arXiv:2012.02445

Betken, A., Giraudo, D., Kulik, R. (2020): Change-point tests for the tail parameter of Long Memory Stochastic Volatility time series. Preprint, arXiv:2006.02667

Betken, A., Wendler, M. (2020): Rank-based change-point analysis for long-range dependent time series. Preprint, arXiv:2004.06574

Betken, A., Buchsteiner, J., Dehling, H., Münker, I., Schnurr, A., Woerner, J. H. C. (2019): Ordinal Patterns in Long-Range Dependent Time Series. Scandinavian Journal of Statistics, doi: 10.1111/sjos.12478

Betken, A. (2017): Change point estimation based on Wilcoxon tests in the presence of long-range dependence. Electronic Journal of Statistics, 11(2), 3633-3672, doi: 10.1214/17-EJS1323

Betken, A., Kulik, R. (2019): Testing for change in stochastic volatility with long range dependence. Journal of Time Series Analysis, 40(5), 707-738, doi: 10.1111/jtsa.12449

Betken, A., Wendler, M. (2018): Subsampling for General Statistics under Long Range Dependence. Statistica Sinica, 28(3), 1199-1224, doi: 10.5705/ss.202015.0435

Betken, A. (2016): Testing for change-points in long-range dependent time series by means of a self-normalized Wilcoxon test. Journal of Time Series Analysis, 37(6), 785-809, doi: 10.1111/jtsa.12187

Research profiles

Address

University of Twente

Zilverling (building no. 11), room 2047
Hallenweg 19
7522 NH Enschede
Netherlands

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