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TRR 391 Publications

Accepted

Bai, L., Hu, Q., Wu, W. (2026). Inference for structural changes in nonstationary functional time series with partial measurement error. To appear in Journal of the Royal Statistical Society Series B: Statistical Methodology.

Li, C., Vehtari, A., Bürkner, P. C., Radev, S. T., Acerbi, L., Schmitt, M. (2026). Amortized Bayesian workflow. To appear in Transactions on Machine Learning Research. Already available on arXiv. DOI: 10.48550/arXiv.2409.04332

Mishra A., Habermann D., Schmitt M., Radev S. T., Bürkner P. C. (2026). Robust amortized Bayesian inference with self-consistency losses on unlabeled data. To appear in ICLR 2026. Already available on OpenReview: https://openreview.net/forum?id=E1dANKwo4I.

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.

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.

Published

Lebedev, A., Das, A., Pappert, S., Schlüter, S. (2026). Analyzing uncertainty quantification in statistical and deep learning models for probabilistic electricity price forecasting. IEEE Access 14, 52162–52189. DOI: 10.1109/ACCESS.2026.3672716.

Uniejewski, B., Ziel, F. (2026). The role of probabilistic load and renewable prediction in enhancing day-ahead electricity price forecasts. Renewable Energy 269, 125844. DOI: 10.1016/j.renene.2026.125844. 

Jakubzik, M. A., Müller, C. H. (2026). Asymptotics of minimum distance estimation for self-exciting load sharing point processes. Statistical Papers 67, 55. DOI: 10.1007/s00362-026-01834-x. 

Bastian, P., Dette, H. (2026). Multiscale detection of practically significant changes in a gradually varying time series. Electronic Journal of Statistics 20 (1), 138–162. DOI: 10.1214/26-EJS2485. 

Kühnert, S., Rice, G. and Aue, A. (2026). Estimating invertible processes in Hilbert spaces, with applications to functional ARMA processes. Bernoulli 32 (2), 1523–1546. DOI: 10.3150/25-BEJ1918. 

Scheurer, S., Reiser P., Brünnette T., Nowak W., Guthke A., Bürkner P. C. (2026). Uncertainty-aware surrogate-based amortized Bayesian inference for computationally expensive models. Transactions on Machine Learning Research. OpenReview: https://openreview.net/forum?id=aVSoQXbfy1. 

Frondel, M., Thiel, P., Vance, C. (2026). The distributional consequences of tax pass-through: the case of Germany's fuel tax discount. Regional Science and Urban Economics 117, 104183. DOI: 10.1016/j.regsciurbeco.2025.104183. 

Säilynoja T., Schmitt M., Bürkner P. C., Vehtari A. (2026). Posterior SBC: simulation-based calibration checking conditional on data. Statistics and Computing 36, 78. DOI: 10.1007/s11222-026-10825-9. 

Ben Amor, S., Ziel, F. (2026). Recurrent neural networks with linear structures for electricity price forecasting. Renewable and Sustainable Energy Reviews 231, 116773. DOI: 10.1016/j.rser.2026.116773. 

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. 

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. 

Keweloh, S., A., Wang, S. (2026). Uncertain short-run restrictions and statistically identified structural vector autoregressions. Journal of Applied Econometrics 41 (1), 12–25. DOI: 10.1002/jae.70012. 

Keweloh, S. A., Wang, S. (2026). Higher moments and efficiency gains in recursive structural vector autoregressions. Oxford Bulletin of Economics and Statistics 88 (1), 36–44 . DOI: 10.1111/obes.70008. 

Golosnoy, V., Gribisch,  B., Schmid, W., Seifert, M. I. (2026). Combining portfolio rules to improve prediction of global minimum variance portfolio weights. The European Journal of Finance 32 (4–6), 510–527 . DOI: 10.1080/1351847X.2025.2512107. 

Lederer, J., von Sachs, R. (2026). Simultaneous estimation of stable parameters for multiple autoregressive processes from datasets of nonuniform sizes. Journal of Time Series Analysis 47 (2), 345–363 . DOI: 10.1111/jtsa.12806. 

Dohme, H., Malchercyzk, D., Leckey, K., Müller, C. H. (2026). K-depth tests for testing simultaneously independence and other model assumptions in time series. Communications in Statistics - Simulation and Computation 55 (3), 657–675. DOI: 10.1080/03610918.2024.2413905. 

Habermann, D., Schmitt, M., Kühmichel, L., Bulling, A., Radev, S. T., Bürkner, P. C. (2025). Amortized Bayesian multilevel models. Bayesian Analysis Advance Publication, 1–30. DOI: 10.1214/25-BA1570. 

Bücher, A., Pakzad, C. (2025). The empirical copula process in high dimensions: Stute's representation and applications. Annals of Statistics 53 (6), 2462–2487. DOI: 10.1214/25-AOS2548. 

Bastian, P. (2025). Choosing the right norm for change point detection in functional data. Electronic Journal of Statistics 19 (2), 4637–4672. DOI: 10.1214/25-EJS2451. 

Heinrichs, F., Bastian, P., Dette, H. (2025). Sequential outlier detection in non-stationary time series. Journal of Time Series Analysis. DOI: 10.1111/jtsa.70043. 

Bastian, P., Basu, R., Dette, H. (2025). Uniform confidence bands for joint angles across different fatigue phases. New Trends in Functional Statistics and Related Fields, 33–42. DOI: 10.1007/978-3-031-92383-8_5. 

Bastian, P. (2025). Detecting relevant deviations from the white noise assumption for non-stationary time series. Journal of Time Series Analysis. DOI: 10.1111/jtsa.70005. 

Elsemüller, L., Pratz, V., von Krause, M., Voss, A., Bürkner, P. C., Radev, S. T. (2025). Does unsupervised domain adaptation improve the robustness of amortized Bayesian inference? A systematic evaluation. Transactions on Machine Learning Research. OpenReview: https://openreview.net/forum?id=ewgLuvnEw6. 

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 [Accelerating environmental policy decisions through reliable data and efficient statistical methods]. AStA Wirtschafts- und Sozialstatistisches Archiv 19, 113–159. DOI: 10.1007/s11943-025-00360-w. 

Gerster, A., Andor, M. A., Goette, L. (2025). Disaggregate consumption feedback. The Economic Journal 136 (675), 1066–1086. DOI: 10.1093/ej/ueaf084. 

Molodchyk, O., Teutsch, J., Faulwasser, T. (2025). Towards safe Bayesian optimization with Wiener kernel regression. 2025 European Control Conference (ECC), 2050–2056. DOI: 10.23919/ECC65951.2025.11187007.

Molodchyk, O., Schmitz, P., Engelmann, A., Worthmann, K., Faulwasser, T. (2025). Towards data driven multi-stage OPF. 2025 IEEE Kiel PowerTech, 1–6. DOI: 10.1109/PowerTech59965.2025.11180719. 

Jeschke, M., Faulwasser, T., Fried, R. (2025). Probabilistic time series forecasting of residential loads - a copula approach. 2025 IEEE Kiel PowerTech, 1–6. DOI: 10.1109/PowerTech59965.2025.11180539. 

Klein, N., Bianco,  N. (2025). Contributed discussion on "Model uncertainty and missing data: An objective Bayesian perspective" by Garcia-Donato et al. Bayesian Analysis 20(4), 1677–1778. DOI: 10.1214/25-BA1531. 

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, 1–19. 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 71 (12), 9647–9673. DOI: 10.1109/TIT.2025.3613143. 

Dzikowski, D., Jentsch, C. (2025). Structural periodic vector autoregressions. Journal of Econometrics Part A 252, 106099. DOI: 10.1016/j.jeconom.2025.106099. 

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 28, 653–676. 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. pdf.

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. pdf.

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. pdf. 

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, 25–32. DOI: 10.1007/978-3-031-92383-8_4. 

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 388, 125444. DOI: 10.1016/j.apenergy.2025.125444. 

Bruns, M., Keweloh S. A. (2024). Testing for strong exogeneity in proxy-VARs. Journal of Econometrics 245 (1–2), 105876. DOI: 10.1016/j.jeconom.2024.105876.  

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