Submitted Papers & Preprints

1. Bae, S., Westphal, C., Ammer, C., Hostert, P., Hüttel, S., Kis-Katos, K., Kneib, T., Kreft, H., Paul, C., Plieninger, T., Putzenlechner, B. M., Roetter, R., Schlund, M., Seidel, D., Siebert, S., Wiegand, K. and Knohl, A. (2025)
   Disentangling Landscape Heterogeneity: Compositional, Configurational, Vertical, and Temporal Heterogeneity by
2. Herp, M., Brachem, J., Altenbuchinger, M. and Kneib, T. (2025)
   Graphical Transformation Models
3. Costa, R., de Sousa, B., Kneib, T., Martins, R. and Mayr, A. (2025)
   Methodological guidance on clinical prediction models in mental health research
4. Gutiérrez-Botella, J., Armero, C., Kneib, T., Pata, M. P. and García-Seara, J. (2025)
   Bayesian competing risks survival modeling for assessing the cause of death of patients with heart failure
5. Hagemann, N., Kneib, T. and Möllenhoff, K. (2025)
   Capturing heterogeneous time-variation in covariate effects in non-proportional hazard regression models
6. Hagemann, N., Guhl, D., Kneib, T., Möllenhoff, K. and Steiner, W. J. (2024)
   Dynamic Heterogeneity in Discrete Choice Experiments
7. Skevas, I. and Kneib, T. (2024)
   A copula-based semiparametric by-production stochastic frontier model
8. Schlee, M., Kant, G., Säfken, B. and Kneib, T. (2024)
   Decoding synthetic news: An interpretable multimodal framework for the classification of news articles in a novel news corpus
9. Bruns, S.B., Herwartz, H., Islam, C.G., Kneib, T. and Malina, R. (2024)
   Ambiguous empirical results are not oversold but more focused on statistical significance
10. Brachem, J., Wiemann, P. F. V. and Kneib, T. (2024)
    Bayesian Penalized Transformation Models: Structured Additive Location-Scale Regression for Arbitrary Conditional Distributions
11. Thielmann, A., Kneib, T. and Säfken, B. (2023)
    Enhancing Adaptive Spline Regression: An Evolutionary Approach to Optimal Knot Placement and Smoothing Parameter Selection
12. Barna, D. M. Engeland, K., Kneib, T., Thorarinsdottir T. L. and Xu, C.-Y. (2023)
    Regional flood frequency analysis at multiple durations: a comparison of duration consistency in quantile and parameter regression techniques
13. Dupont, E., Marques, I. and Kneib, T. (2023)
    Demystifying Spatial Confounding
14. Kruse, R.-M., Säfken, B. and Kneib, T. (2023)
    Measuring Neural Complexity: A Covariance Penalty Approach
15. Thielmann, A., Kruse, R.-M., Kneib, T. and Säfken, B. (2023)
    Neural Additive Models for Location Scale and Shape: A Framework for Interpretable Neural Regression Beyond the Mean
16. Nadifar, M., Baghishani, H., Kneib, T. and Fallah, A. (2022)
    Flexible Bayesian modeling of counts: constructing penalized complexity priors
17. Riebl, H., Wiemann, P. F. V. and Kneib, T. (2022):
    Liesel: A Probabilistic Programming Framework for Developing Semi-Parametric Regression Models and Custom Bayesian Inference Algorithms