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TRR 391 Publications

Accepted

Amor, S. B., Ziel, F. (2026). Recurrent Neural Networks with Linear Structures for Electricity Price Forecasting. To appear in Renewable and Sustainable Energy Reviews. Already available on arXiv. DOI: 10.48550/arXiv.2512.04690.

Bürkner, P. C., Schmitt M., Radev S. T. (2026). Simulations in statistical workflows. To appear in Philosophical Transactions A. Already available on arXiv. DOI: 10.48550/arXiv.2503.24011.

Säilynoja T., Schmitt M., Bürkner P. C., Vehtari A. (2026). Posterior SBC: simulation-based calibration checking conditional on data. To appear in Statistics and Computing. Already available on arXiv. DOI: 10.48550/arXiv.2502.03279.

Frondel, M., Thiel, P., Vance, C. (2026). The Distributional Consequences of Tax Pass-Through: The Case of Germany's Fuel Tax Discount. To appear in Regional Science and Urban Economics.

Ickstadt, K., Breitner-Busch, S., Conrad, A., Diekmann, A., Elmer, C., Felgendreher, S., Fried, R., Friedrich, S., Fuks, K., Groll, A., Hense, A., Hornberg, C., Küchenhoff, H., Leitgöb, H., Paetz, F., Radermacher, W. J., Schürz, S., Wolf, K. (2025). Beschleunigung umweltpolitischer Entscheidungen durch verlässliche Daten und effiziente statistische Methoden. To appear in AStA Advances in Statistical Analysis.

Klein, N., Bianco,  N. (2025). Contributed discussion on "Model uncertainty and missing data: An objective Bayesian perspective" by Garcia-Donato et al. To appear in Bayesian Analysis.

Bücher, A., Dette, H. (2025). On the lack of weak continuity of Chatterjee's correlation coefficient. To appear in Statistical Science. Already available on arXiv. DOI: 10.48550/arXiv.2410.11418.

Bücher, A., Pakzad C. (2025). The empirical copula process in high dimensions: Stute's representation and applications. To appear in Annals of Statistics. Already available on arXiv. DOI: 10.48550/arXiv.2405.05597.

Jeschke, M., Faulwasser, T., Fried, R. (2025). Probabilistic Time Series Forecasting of Residential Loads - A Copula Approach.  To appear in 2025 IEEE Kiel PowerTech. Already available on arXiv. DOI: 10.48550/arXiv.2504.21661.

Published

Feldhaus, C., Lingens, J., Löschel, A., Zunker, G. (2026). Measuring the intrinsic value of choice. European Economic Review 184, 105254. DOI: 10.1016/j.euroecorev.2025.105254.

Habermann, D., Schmitt, M., Kühmichel, L., Bulling, A., Radev, S. T., Bürkner, P. C. (2026). Amortized Bayesian Multilevel Models. Bayesian Analysis. DOI: 10.1214/25-BA1570.

Ghelasi, P., Ziel, F. (2026). A data-driven merit order: Learning a fundamental electricity price model. Energy Economics 154, 109114. DOI: 10.1016/j.eneco.2025.109114.

Ghelasi, P., Ziel, F. (2025). From day-ahead to mid and long-term horizons with econometric electricity price forecasting models. Renewable and Sustainable Energy Reviews 217, 115684. DOI: 10.1016/j.rser.2025.115684.

Axt, I., Fried, R. (2025). Robust scale estimation for strongly mixing processes under shifts in the mean. Statistics - a Journal of Theoretical and Applied Statistics. DOI: 10.1080/02331888.2025.2600463.

Schumacher, F. L., Knoth, C., Ludwig, M., Meyer, H. (2025). Estimation of local training data point densities to support the assessment of spatial prediction uncertainty. Geoscientific Model Development 18 (24), 10185–10202. DOI: 10.5194/gmd-18-10185-2025.

Taheri, M., Xie, F., Lederer, J. (2025). Statistical Guarantees for Approximate Stationary Points of Shallow Neural Networks. Transactions on Machine Learning Research. OpenReview: https://openreview.net/forum?id=PNUMiLbLml.

Hebiri, M., Lederer, J., Taheri, M. (2025). Layer sparsity in neural networks. Journal of Statistical Planning and Inference 234, 106195. DOI: 10.1016/j.jspi.2024.106195.

Damm, S., Laszkiewicz, M., Lederer, J., Fischer, A. (2025). AnomalyDINO: Boosting Patch-based Few-shot Anomaly Detection with DINOv2. IEEE/CVF Winter Conference on Applications of Computer Vision. pdf. DOI: 10.48550/arXiv.2405.14529.

Mohaddes, A., Lederer, J. (2025). Cardinality Sparsity: Applications in Matrix-Matrix Multiplications and Machine Learning. Transactions on Machine Learning Research. OpenReview: https://openreview.net/forum?id=zoSRSpGu9C.

Kucharský, Š., Mishra, A., Habermann, D., Radev, S. T., Bürkner, P. C. (2025). Towards Trustworthy Amortized Bayesian Model Comparison. NeurIPS Workshop on Reliable Machine Learning from Unreliable Data. OpenReview: https://openreview.net/forum?id=6lMb0itvl0.

Gierse, J., Fried, R. (2025). Nonparametric directional variogram estimation in the presence of outlier blocks. Statistical Papers 66, 134. DOI: 10.1007/s00362-025-01754-2.

Kock, L., Klein, N., Nott, D.J. (2025). Deep Mixture of Linear Mixed Models for Complex Longitudinal Data. Statistics in Medicine 44, 23-24. e70288. DOI: 10.1002/sim.70288.

Demetrescu, M., Frondel, M., Tomberg, L., Vance, C. (2025). Fixed Effects, Lagged Dependent Variables, and Bracketing: Cautionary Remarks. Political Analysis 33 (4), 378–392. DOI: 10.1017/pan.2025.10002.

Bai, L., Wu, W. (2025). Uniform variance reduced simultaneous inference of time-varying correlation networks. IEEE Transactions on Information Theory. DOI: 10.1109/TIT.2025.3613143.

Keweloh, S., A., Wang, S. (2025). Uncertain Short-Run Restrictions and Statistically Identified Structural Vector Autoregressions. Journal of Applied Econometrics, 1–14. DOI: 10.1002/jae.70012.

Dzikowski, D., Jentsch, C. (2025). Structural Periodic Vector Autoregressions. Journal of Econometrics 252 (A), 106099. DOI: 10.1016/j.jeconom.2025.106099.

Keweloh, S. A., Wang, S. (2025). Higher Moments and Efficiency Gains in Recursive Structural Vector Autoregressions. Oxford Bulletin of Economics and Statistics , 1–9. DOI: 10.1111/obes.70008.

Golosnoy, V., Gribisch,  B., Schmid, W., Seifert, M. I. (2025). Combining portfolio rules to improve prediction of global minimum variance portfolio weights. The European Journal of Finance, 1–18. DOI: 10.1080/1351847X.2025.2512107.

Seifert, M. I. (2025). Which distributions in the max-domain of attraction satisfy von Mises representation or variation representation for a given auxiliary function? Extremes. DOI: 10.1007/s10687-025-00516-5.

Andor, M. A., Dehos, F., Gillingham, K., Hansteen, S., Tomberg, L. (2025). Public transport pricing: An evaluation of the 9-Euro Ticket and an alternative policy proposal. Economics of Transportation 42, 100415. DOI: 10.1016/j.ecotra.2025.100415.

Kaiser, S., Klein, N., Kaack, L. (2025). From counting stations to city-wide estimates: Data-driven bicycle volume extrapolation. Environmental Data Sciene 4 (13), 1–43. DOI: 10.1017/eds.2025.5.

Yuan, Z., Spindler, M. (2025). Bernstein-type inequalities and nonparametric estimation under near-epoch dependence. Journal of Econometrics 251, 106054. DOI: 10.1016/j.jeconom.2025.106054. 

Ben Amor, S., Ziel, F. (2025). Combining RNN and Linear Structures in Day-Ahead Electricity Price Forecasting. Proceedings of the 39th International Workshop on Statistical Modelling, Volume 1.

Grytzka, J., Bürkner, P., Groll, A. (2025). LASSO penalization in generalized linear mixed models. Proceedings of the 39th International Workshop on Statistical Modelling, Volume 1.

Stroemer, A., de Carvalho, M., Klein, N., Mayr, A. (2025). Modeling joint extreme events via boosting distributional copula regression. Proceedings of the 39th International Workshop on Statistical Modelling, Volume 1.

Golestaneh, P., Taheri, M., Lederer, J. (2025). How many samples are needed to train a deep neural network? ICLR 2025. pdf. DOI: 10.48550/arXiv.2405.16696. 

Faymonville, M., Jentsch, C., Weiß, C.H. (2025). Semi-parametric goodness-of-fit testing for INAR models. Bernoulli 31 (4), 3213-3234. DOI: 10.3150/24-BEJ1844.

Frondel, M., Helmers, V., Sommer, S. (2025). Fostering the Acceptance of Congestion Charges: Experimental Evidence for Europe. Journal of Transport Economics and Policy 59 (3), 161–178.

Helmers, V., van der Werf, E. (2025). Did the German Aviation Tax Have a Lasting Effect on Passenger Numbers? Transportation Research Part D: Transport and Environment 140, 104570. DOI: 10.1016/j.trd.2024.104570.

Aue, A., Kühnert, S., Rice, G. (2025). On the Estimation of Invertible Functional Time Series. New Trends in Functional Statistics and Related Fields. IWFOS 2025. Contributions to Statistics. DOI: 10.1007/978-3-031-92383-8_4.

Bruns, M., Keweloh S. A. (2025). Testing for strong exogeneity in proxy-VARs. Journal of Econometrics 245 (1-2). DOI: 10.1016/j.jeconom.2024.105876. 

Demetrescu, M., Hillmann, B. (2025). Gaussian inference in predictive regressions for stock returns. Journal of Financial Econometrics 23 (2), nbaf004. DOI: 10.1093/jjfinec/nbaf004. 

Zimmermann, M., Ziel, F. (2025). Efficient mid-term forecasting of hourly electricity load using generalized additive models. Applied Energy. DOI: 10.1016/j.apenergy.2025.125444.

Lederer, J., von Sachs, R. (2025). Simultaneous estimation of stable parameters for multiple autoregressive processes from datasets of nonuniform sizes. Journal of Time Series Analysis. DOI: 10.1111/jtsa.12806.

Dohme, H., Malchercyzk, D., Leckey, K., Müller, C. H. (2024). K-depth tests for testing simultaneously independence and other model assumptions in time series. Communications in Statistics - Simulation and Computation, 1–19. DOI: 10.1080/03610918.2024.2413905.

Hanck, C., Massing, T. (2024). Testing for nonlinear cointegration under heteroskedasticity. Econometric Reviews 44 (4), 512–543. DOI: 10.1080/07474938.2024.2429598.