Statistisches Beratungslabor






  • Spatio-Temporal Data Analysis
  • Age-Period-Cohort Analysis
  • Image Classification
  • Predictive Modelling


  • Wolffram, D., Abbott, S., an der Heiden, M., Funk, S., Günther, F.,  Hailer, D., Heyder, S., Hotz, T., van de Kassteele, J., Küchenhoff, H., Müller-Hansen, S., Syliqi, D., Ullrich, A., Weigert, M., Schiele, M., and Bracher, J. (2023) Collaborative nowcasting of COVID-19 hospitalization incidences in Germany. PLOS Computational Biology 19(8): e1011394. doi:10.1371/journal.pcbi.1011394.
  • Reinkemeyer, C., Khazaei, Y., Weigert, M., Hannes, M., Le Gleut, R., Plank, M., Winter, S., Noreña, I., Meier, T., Xu, L., Rubio-Acero, R., Wiegrebe, S., Thi, T.G.L., Fuchs, C., Radin, K., Paunovic, I., Janke, C., Wieser, A., Küchenhoff, H., Hoelscher, M., and Castelletti, N. (2023). The Prospective COVID-19 Post-Immunization Serological Cohort in Munich (KoCo-Impf): Risk Factors and Determinants of Immune Response in Healthcare Workers. Viruses, 15(7), 1574. doi:10.3390/v15071574.
  • Jörgens, M., Brunner, J., Weigert, M., Bormann, M., Böhm, E., Böcker, W., Paulus, A.C., Ehrl, D., and Fuermetz, J. (2023). Linear correlation between patellar positioning and rotation of the lower limb in radiographic imaging: a 3D simulation study. Knee Surgery, Sports Traumatology, Arthroscopy, 1-7. doi:10.1007/s00167-022-07302-x.
  • Weigert, M., Beyerlein, A., Katz, K., Schulte, R., Hartl, W., and Küchenhoff, H. (2023): Vaccine-induced or hybrid immunity and COVID-19-associated mortality during the Omicron wave—a retrospective observational study in the elderly. Dtsch Arztebl Int 2023; 120(13), 213. doi:10.3238/arztebl.m2023.0051.
  • Brunner, J., Jörgens, M., Weigert, M., Kümpel, H., Degen, N., and Fuermetz, J. (2023). Significant changes in lower limb alignment due to flexion and rotation—a systematic 3D simulation of radiographic measurements. Knee Surgery, Sports Traumatology, Arthroscopy, 1-8. doi:10.1007/s00167-022-07302-x.
  • Fritz, C., De Nicola, G., Rave, M., Weigert, M., Khazaei, Y., Berger, U., Küchenhoff, H., and Kauermann, G. (2022). Statistical modelling of COVID-19 data: Putting generalized additive models to work. Statistical Modelling. doi:10.1177/1471082X221124628.
  • Fritz, C., De Nicola, G., Günther, F., Rügamer, D., Rave, M., Schneble, M., Bender, A., Weigert, M., Brinks, R., Hoyer, A., Berger, U., Küchenhoff, H., and Kauermann, G. (2022). Challenges in Interpreting Epidemiological Surveillance Data – Experiences from Germany. Journal of Computational and Graphical Statistics. doi:10.1080/10618600.2022.2126482.
  • Mittermeier, M., Weigert, M., Rügamer, D., Küchenhoff, H., and Ludwig, R. (2022). A deep learning based classification of atmospheric circulation types over Europe: projection of future changes in a CMIP6 large ensemble. Environmental Research Letters, 17. doi:10.1088/1748-9326/ac8068.
  • Bauer, A., Weigert, M., and Jalal, H. (2022). APCtools: Descriptive and Model-based Age-Period-Cohort Analysis. Journal of Open Source Software, 7(73), 4056. doi:10.21105/joss.04056.
  • Zumeta-Olaskoaga, L., Weigert, M., Larruskain, J., Bikandi, E., Setuain, J., Lekue, J., Küchenhoff, H., and Lee, D.-J. (2021). Prediction of sports injuries in football: a recurrent time-to-event approach using regularized Cox models. AStA Adv Stat Anal. doi:10.1007/s10182-021-00428-2
  • Mittermeier, M., Weigert, M., and Rügamer, D. (2021). Identifying the atmospheric drivers of drought and heat using a smoothed deep learning approach. NeurIPS 2021, Tackling Climate Change with Machine Learning. arXiv:2111.05303.
  • Weigert, M., Bauer, A., Gernert, J., Karl, M., Nalmpatian, A., Küchenhoff, H., and Schmude, J. (2021). Semiparametric APC analysis of destination choice patterns: Using generalized additive models to quantify the impact of age, period, and cohort on travel distances. Tourism Economics. doi:10.1177/1354816620987198.
  • Keppler, A. M., Küßner, K., Schulze, A. L., Suero, E. M., Neuerburg, C., Weigert, M., Braun, C., Böcker, W., Kammerlander, C., and Zeckey, C. (2021). Radiographic cortical thickness parameters as predictors of rotational alignment in proximal tibial shaft fractures: a cadaveric study. BMC Musculoskeletal Disorders, 22(1), 1-11. doi:10.1186/s12891-021-04452-w.
  • Zeckey, C., Späth, A., Kieslich, S., Kammerlander, C., Böcker, W., Weigert, M., and Neuerburg, C. (2020). Early Mobilization Versus Splinting After Surgical Management of Distal Radius Fractures: Results of a Randomized Controlled Study of Postoperative Care in Older Patients. Deutsches Ärzteblatt International. doi: 10.3238/arztebl.2020.0445.


  • R-Paket fuzzyclara: Efficient and fuzzy clustering based on the CLARA algorithm (GitHub).
  • R-Paket APCtools: Routines for Descriptive and Model-Based APC Analysis (GitHub, CRAN).

Präsentationen und Poster

  • Weigert, M., Mittermeier, M., Rügamer, D., Küchenhoff, H., and Ludwig, R. (2022). Classification of atmospheric circulation patterns using a smoothed deep learning approach. In DAGStat Conference, 2022, Hamburg.
  • Weigert, M., Bauer, A., Gernert, J., Karl, M., Küchenhoff, H., and Schmude, J. (2020). Visualization techniques for semiparametric APC analysis–Using Generalized Additive Models to examine touristic travel distances. In 35th International Workshop on Statistical Modelling 2020, online (p. 450).
  • Schmude, J., Weigert, M., Bauer, A., Karl, M., Gernert, J., Küchenhoff, H., and Bartl, E. (2020). Spatio-temporal changes in travel behavior: Analyzing external and internal temporal effects on destination choices. In Consumer Behavior in Tourism Symposium–CBTS, 2020, online. ZPID (Leibniz Institute for Psychology).


  • R and SAS - A Benchmarking Analysis in the Context of Machine Learning for Binary Classification Problems
    Master of Science, Ludwig-Maximilians-Universität München (2017).
  • Ökologische Inferenz bei der Vergabe von Erst- und Zweitstimme bei Bundestagswahlen in Deutschland - Ein Vergleich verschiedener Methoden
    Bachelor of Science, Ludwig-Maximilians-Universität München (2015).