Dr. Tim Kutta

• Dunsche, M., Kutta, T. und Dette, H. (2022).
  Multivariate Mean Comparison Under Differential Privacy. 
  Privacy in Statistical Databases 2022, 31-45
• Askin, Ö., Kutta, T. und Dette, H. (2022).
  Statistical quantification of differential privacy: A local approach. 
  2022 IEEE Symposium on Security and Privacy, 402-421
• Kutta, T., Dierickx, G. und Dette, H. (2022).
  Statistical inference for the slope parameter in functional linear regression. 
  Electronic Journal of Statistics, 16(2), 5980-6042
• Dette, H., Dierickx, G. und Kutta, T. (2022).
  Quantifying deviations from separability in space-time functional processes. 
  Bernoulli, 28(4), 2909-2940
• Dette, H. und Kutta, T. (2021).
  Detecting structural breaks in eigensystems of functional time series. 
  Electronic Journal of Statistics, 15(1), 944-983
• Kutta, T., Bissantz, N., Chown, J., und Dette, H. (2019).
  The Empirical Process of Residuals from an Inverse Regression. 
  Mathematical Methods of Statistics, 28(2), 104–126

Eingereicht

• Askin, Ö., Dunsche, M. und Kutta, T. (2022).
  Lower Bounds for Rényi Differential Privacy in a Black-Box Setting.
  arXiv: 2212.04739 
• Dette, H., Kutta, T. (2022).
  Validating Approximate Slope Homogeneity in Large Panels.
  arXiv: 2205.02197 

Abschlussarbeiten

• Pivotal goodness-of-fit measures in functional data analysis.
  Dissertation Mathematik, Ruhr-Universität Bochum, April 2022
  Prof. Dr. Holger Dette
• The empirical residual process in an inverse regression model.
  Masterarbeit Mathematik, Ruhr-Universität Bochum, 2018
  Prof. Dr. Holger Dette
• Der isonormale Gaußprozess.
  Bachelorarbeit Mathematik, Ruhr-Universität Bochum, 2016
  Prof. Dr. Angelika Rohde

• Gutachter für Bernoulli
• Gutachter für Journal of the American Statistical Association