Josua Gösmann
Ruhr-Universität Bochum
Department of Mathematics
Institute of Statistics
Building IB 2/69
Universitätsstrasse 150
D-44801 Bochum
Tel.: +49 (0)234 / 32 23288
Fax: +49 (0)234 / 32 14559
E-Mail: josua dot goesmann at ruhr-uni-bochum.de
Office hours
by appointment
Research interests
- High-dimensional statistics
- Time series
Publications
Gösmann, J., Kley, T. and Dette, H. (2020+)
A new approach for open-end sequential change point monitoring.
To appear in: Journal of the Time Series Analysis.
Dette, H. and Gösmann, J. (2019+).
A likelihood ratio approach to sequential change point detection for a general class of parameters.
To appear in: Journal of the American Statistical Association.
Dette, H., Konstantinou, M., Schorning, K. and Gösmann, J. (2019).
Optimal designs for regression with spherical data.
Electronic Journal of Statistics 13(1), 361-390.
Dette, H. and Gösmann, J. (2018).
Relevant change points in high dimensional time series.
Electronic Journal of Statistics 12, 2578-2636.
Gösmann, J. and Ziggel, D. (2018).
An innovative risk management methodology for trading equity indices based on change points.
Journal of Asset Management 19(2), 99-109.
Dette, H., Gösmann, J., Greiff, C. and Janisch, R. (2017).
Efficient sampling in materials simulation - Exploring the parameter space of grain boundaries.
Acta Materialia 125, 145-155.
Submitted:
Gösmann, J., Stoehr, C. and Dette, H. (2020)
Sequential change point detection in high dimensional time series.
Submitted for publication: (PDF).
Theses
Strukturbruchtests für hochdimensionale Daten.
Master thesis Mathematics, Ruhr-Universität Bochum, 2016
Journals
- Reviewer for Annals of Statistics
- Reviewer for Journal of Statistical Planning and Inference
- Reviewer for Quantitative Finance