Thesis/Theses examined by Heumann, Christian

Scholbeck, Christian Alexander (2024): Bridging gaps in interpretable machine learning: sensitivity analysis, marginal effects, and cluster explanations. Dissertation, LMU München: Faculty of Mathematics, Computer Science and Statistics

Li, Linwei (2022): A model-based reinforcement learning framework for optimal liquidation of foreign currencies. Dissertation, LMU München: Faculty of Mathematics, Computer Science and Statistics

Aßenmacher, Matthias (2021): Comparability, evaluation and benchmarking of large pre-trained language models. Dissertation, LMU München: Faculty of Mathematics, Computer Science and Statistics

Razzak, Humera (2020): Multiple imputation of large scale complex surveys. Dissertation, LMU München: Faculty of Mathematics, Computer Science and Statistics

Speidel, Matthias (2018): Imputation for hierarchical datasets and responses in intervals. Dissertation, LMU München: Faculty of Mathematics, Computer Science and Statistics

Bayerstadler, Andreas (2017): Application of modern statistical methods in worldwide health insurance. Dissertation, LMU München: Faculty of Mathematics, Computer Science and Statistics

Seiler, Christian (2013): Nonresponse in business tendency surveys: theoretical discourse and empirical evidence. Dissertation, LMU München: Faculty of Mathematics, Computer Science and Statistics

Meinel, Michael (2006): Nichparametrische, Semiparametrische und SUR-Modelle für stetige Longitudinaldaten. Dissertation, LMU München: Faculty of Mathematics, Computer Science and Statistics