Submitted Papers & Preprints

1. Kneib, T., Schlüter, J. C. and Wacker, B. (2025)
   Global existence and global uniqueness of maximum log-likelihood estimation of two-parameter Inverse Weibull distributions - Analysis and applications
2. Hüllen, T., Witforth, S. and Kneib, T. (2025)
   Behind the Curtain: Technology Maturity Estimation Using Hidden Markov Models
3. Henrich, J., Pos, C., Zilke, M., Shiroya, P., Chanut, E., Yamchi, A. M., Yahyapour, R., Kneib, T. and Traulsen, I. (2025)
   Benchmarking pig detection and tracking under diverse and challenging conditions
4. Rosero, G., Schmidt, R., Kneib, T. and Brümmer, B. (2025)
   Semiparametric stochastic frontier analysis accounting for spatial dependency. A countrywide analysis of Ecuadorian cocoa producers
5. 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
6. Herp, M., Brachem, J., Altenbuchinger, M. and Kneib, T. (2025)
   Graphical Transformation Models
7. Costa, R., de Sousa, B., Kneib, T., Martins, R. and Mayr, A. (2025)
   Methodological guidance on clinical prediction models in mental health research
8. 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
9. Hagemann, N., Kneib, T. and Möllenhoff, K. (2025)
   Capturing heterogeneous time-variation in covariate effects in non-proportional hazard regression models
10. Hagemann, N., Guhl, D., Kneib, T., Möllenhoff, K. and Steiner, W. J. (2024)
    Dynamic Heterogeneity in Discrete Choice Experiments
11. Skevas, I. and Kneib, T. (2024)
    A copula-based semiparametric by-production stochastic frontier model
12. 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
13. 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
14. Brachem, J., Wiemann, P. F. V. and Kneib, T. (2024)
    Bayesian Penalized Transformation Models: Structured Additive Location-Scale Regression for Arbitrary Conditional Distributions
15. Thielmann, A., Kneib, T. and Säfken, B. (2023)
    Enhancing Adaptive Spline Regression: An Evolutionary Approach to Optimal Knot Placement and Smoothing Parameter Selection
16. 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
17. Dupont, E., Marques, I. and Kneib, T. (2023)
    Demystifying Spatial Confounding
18. Kruse, R.-M., Säfken, B. and Kneib, T. (2023)
    Measuring Neural Complexity: A Covariance Penalty Approach
19. 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
20. Nadifar, M., Baghishani, H., Kneib, T. and Fallah, A. (2022)
    Flexible Bayesian modeling of counts: constructing penalized complexity priors
21. 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