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Published in Journal 1, 2010
This paper is about the number 2. The number 3 is left for future work.
Recommended citation: Your Name, You. (2010). "Paper Title Number 2." Journal 1. 1(2). http://academicpages.github.io/files/paper2.pdf
Published in Journal 1, 2015
This paper is about the number 3. The number 4 is left for future work.
Recommended citation: Your Name, You. (2015). "Paper Title Number 3." Journal 1. 1(3). http://academicpages.github.io/files/paper3.pdf
Published in Heinrich-Heine-University Düsseldorf, 2020
In this thesis the Domain of Attraction of the Gumbel distribution is fully characterized.
Recommended citation: Staud, T. (2020). "The Gumbel Max-Domain of Attraction in Extremes "
Published in Heinrich-Heine-University Düsseldorf, 2021
In this thesis a new class of limit distributions from (M. L. Stein, 2017, Biometrika) is investigated.
Recommended citation: Staud, T. (2020). " Block Maxima for Time Series with Varying Upper Bound "
Published in Electronic Journal of Statistics, 2024
In this paper U-statistics of multivariate disjoint and sliding block maxima for time series are considered. Limit theorems and finite-sample simulation studies are presented.
Recommended citation: Bücher, A., Staud, T. (2024). "Limit theorems for non-degenerate U-statistics of block maxima for time series " Electron. J. Statist. 18(2): 2850-2885.
Published in Statistics & Probability Letters, 2024
We prove a formula for the maximal correlation coefficient of the bivariate Marshall Olkin distribution that was conjectured in Lin, Lai, and Govindaraju (2016, Stat. Methodol., 29:1–9).
Recommended citation: Bücher, A., Staud, T. (2025). "On the maximal correlation coefficient for the bivariate Marshall Olkin distribution" Statistics and Probability Letters, Vol. 219, 110323.
Published in Ruhr-University Bochum, 2024
In this thesis novel results on both the sliding and disjoint block maxima method are presented.
Recommended citation: Staud, T. (2025). " On the Sliding Block Maxima Method in Extreme Value Statistics "
Published in Journal of the Royal Statistical Society, Series B (Statistical Methodology), 2025
In this paper bootstrapping of block maxima estimators is considered. Consistency results and limit theorems are provivded. Large scale High Performance Cluster-powered simulation studies are conducted. The application is demonstrated via a case study involving precipation extremes at a weather station in Germany.
Recommended citation: Bücher, A., Staud, T. (2025). "Bootstrapping Estimators based on the Block Maxima Method" To appear in: Journal of the Royal Statistical Society, Series B (Statistical Methodology)
Published:
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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