Submitted Papers & Preprints

1. Aschersleben, P., Granna, J., Kneib, T., Lang, S., Umlauf, N. and Steiner, W. (2026)
   Modelling multiplicative interaction effects in Gaussian structured additive regression models
2. Aschersleben, P., Kneib, T., Lang, S. and Steiner, W. (2026)
   Improving Brand Sales Forecasts: A Reparametrization Approach to Capture Time-Varying Price Effects in Semiparametric Sales Response Models
3. Groll, A., Iannario, M., Kneib, T. and Umlauf, N. (2026)
   Regularized Structured Additive Models for Ordinal Data with a Don’t Know Response Option
4. de Queiroz, F. F., Brachem, , J., Wiemann, P. and Kneib, T. (2026)
   Bayesian structured additive quantile regression for inflated bounded data
5. Cieply, I., Barros, L., Kneib, T., Silbersdorff, A., Kis-Katos, K. (2026)
   Why Female Professors Earn Less: The Role of Retention Negotiations and Performance Bonuses
6. Brito, A. L., De Bastiani, F., Stasinopoulos, M. D., Rigby, R. A.,Manghi, R. F. and Kneib, T. (2025)
   Exploring and comparing pairwise nonlinear association measures for continuous variables
7. Habereder, I., Kneib, T., Echizen, I. and Spinde, T. (2025)
   A Systematic Review of Spatio-Temporal Statistical Models: Theory, Structure, and Applications
8. Mallick, S., Lichter, J., Bae, S., Kneib, T., Molleman, F., Leroy, B. M. L., Hilmers, T., Huszarik, M., Liebhold, A. M., Weisser, W. W., Jehle, J. A., Müller, J. and Prinzing, A. (2025)
   Forest trees delay budburst across landscapes to escape herbivory
9. 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
10. Hüllen, T., Witforth, S. and Kneib, T. (2025)
    Behind the Curtain: Technology Maturity Estimation Using Hidden Markov Models
11. 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
12. 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)
    Landscape Heterogeneity is Structured by Multidimensional Components and Land-Cover Proportion Interactions
13. Herp, M., Brachem, J., Altenbuchinger, M. and Kneib, T. (2025)
    Graphical Transformation Models
14. Costa, R., de Sousa, B., Kneib, T., Martins, R. and Mayr, A. (2025)
    Methodological guidance on clinical prediction models in mental health research
15. Hagemann, N., Kneib, T. and Möllenhoff, K. (2025)
    Capturing heterogeneous time-variation in covariate effects in non-proportional hazard regression models
16. Hagemann, N., Guhl, D., Kneib, T., Möllenhoff, K. and Steiner, W. J. (2024)
    Dynamic Heterogeneity in Discrete Choice Experiments
17. 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
18. Brachem, J., Wiemann, P. F. V. and Kneib, T. (2024)
    Bayesian Penalized Transformation Models: Structured Additive Location-Scale Regression for Arbitrary Conditional Distributions
19. 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
20. Dupont, E., Marques, I. and Kneib, T. (2023)
    Demystifying Spatial Confounding
21. Kruse, R.-M., Säfken, B. and Kneib, T. (2023)
    Measuring Neural Complexity: A Covariance Penalty Approach
22. 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