Institute of Statistics

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