Dominik Liebl

Bio

• 2026–presentFull Professor of Statistics at the Catholic University of Eichstätt-Ingolstadt
• 2020–2026Professor of Statistics at the Institute of Finance and Statistics, University of Bonn
• 2014–2020Assistant Professor of Statistics at the Institute of Finance and Statistics, University of Bonn
• 2019Research Visit (March) at the Simons Institute for the Theory of Computing, UC Berkeley
• 2013–2014Postdoctoral Researcher at the European Center for Advanced Research in Economics and Statistics, Université Libre de Bruxelles
• 2010Research Visit, Working Group STAPH, Université Toulouse III – Paul Sabatier
• 2008–2010PhD at the Institute for Econometrics and Statistics, University of Cologne

Publications

Working Papers

• Fang, C. and Liebl, D. Making event study plots honest: A functional data approach to causal inference. Under review. PDF
• Ofner, M., Hörmann, S., Kraus, D. and Liebl, D. Testing the missing completely at random assumption for functional data. Under review. PDF
• Creutzinger, M., Liebl, D., Mensinger, T. and Sharp, J. Adaptive simultaneous prediction bands in concurrent functional linear regression. Under review. PDF
• Kneip, A., Liebl, D. and Otto, S. Combining concurrent and historical functional linear regression. Work in progress.
• Telschow, F. J. E. and Liebl, D. Generalized Kac-Rice formulas for non-constant critical value functions. Work in progress.

Publications in Statistics

• Liebl, D. and Reimherr, M. (2023). Fast and fair simultaneous confidence bands for functional parameters. Journal of the Royal Statistical Society, Series B, 85(3), 842–868. PDFR package
• Pataky, T. C., Abramowicz, K., Liebl, D., Pini, A., Sjöstedt de Luna, S. and Schelin, L. (2023). Simultaneous inference for functional data in sports biomechanics: Comparing statistical parametric mapping with interval-wise testing. AStA Advances in Statistical Analysis, 107, 369–392. Code
• Bada, O., Kneip, A., Liebl, D., Mensinger, T., Gualtieri, J. and Sickles, R. C. (2022). A wavelet method for panel models with jump discontinuities in the parameters. Journal of Econometrics, 226(2), 399–422. PDFSupplementR packageCode
• Poß, D., Liebl, D., Kneip, A., Eisenbarth, H., Wager, T. D. and Feldman Barrett, L. (2020). Super-consistent estimation of points of impact in nonparametric regression with functional predictors. Journal of the Royal Statistical Society, Series B, 82(4), 1115–1140. PDFR package
• Liebl, D., Rameseder, S. and Rust, C. (2020). Improving estimation in functional linear regression with points of impact: Insights into Google AdWords. Journal of Computational and Graphical Statistics, 29(4), 814–826. PDFR package
• Kneip, A. and Liebl, D. (2020). On the optimal reconstruction of partially observed functional data. The Annals of Statistics, 48(3), 1692–1717. PDFR package
• Liebl, D. (2019). Nonparametric testing for differences in electricity prices: The case of the Fukushima nuclear accident. The Annals of Applied Statistics, 13(2), 1128–1146. PDFSupplementCode & Data
• Liebl, D. and Rameseder, S. (2019). Partially observed functional data: The case of systematically missing parts. Computational Statistics & Data Analysis, 131, 104–115. PDFR package
• Liebl, D. and Walders, F. (2019). Parameter regimes in partial functional panel regression. Econometrics and Statistics, 11, 105–115. PDFSupplement
• Liebl, D. (2019). Inference for sparse and dense functional data with covariate adjustments. Journal of Multivariate Analysis, 170, 315–335. PDF
• Bada, O. and Liebl, D. (2014). phtt: Panel data analysis with heterogeneous time trends in R. Journal of Statistical Software, 59(6), 1–33. R package
• Liebl, D. (2013). Modeling and forecasting electricity prices: A functional data perspective. The Annals of Applied Statistics, 7(3), 1562–1592. PDFCode & Data

Book Chapters & Editorials

• Groll, A. and Liebl, D. (2023). Editorial special issue: Statistics in sports. AStA Advances in Statistical Analysis, 107, 1–7.
• Liebl, D. and Reimherr, M. (2020). Simultaneous inference for function-valued parameters: A fast and fair approach. In: Functional and High-Dimensional Statistics and Related Fields, edited by Aneiros, G., Horová, I., Hušková, M. and Vieu, P., pp. 153–159.
• Walders, F. and Liebl, D. (2017). Parameter regimes in partially functional linear regression for panel data. In: Functional Statistics and Related Fields, edited by Aneiros, G., Bongiorno, E. G., Cao, R. and Vieu, P., pp. 261–270.
• Liebl, D. and Kneip, A. (2014). Modelling electricity prices as functional data on random domains. In: Contributions in Infinite-Dimensional Statistics and Related Topics, edited by Bongiorno, E. G., Salinelli, E., Goia, A. and Vieu, P., pp. 90–97.
• Liebl, D., Mosler, K. and Willwacher, S. (2012). Robust clustering of joint moment curves. In: 9. Symposium der Sektion Sportinformatik der Deutschen Vereinigung für Sportwissenschaft, edited by Byshko, R., Dahmen, T., Gratkowski, M., Gruber, M., Quintana, J., Saupe, D., Vieten, M. and Woll, A., pp. 68–73.

Further Publications

• Richter, E., Liebl, D., Schulte, B., Lehmann, N., Fuhrmann, C., Jöckel, K.-H., Ioannidis, J. P. A. and Streeck, H. (2023). Analysis of fatality impact and seroprevalence surveys in a community sustaining a SARS-CoV-2 superspreading event. Scientific Reports, 13, 5440.
• Liebl, D. (2022). Letter to the Editor on: “Comparing groups of time dependent data using locally weighted scatterplot smoothing alpha-adjusted serial t-tests” by Niiler (2020). Gait & Posture, 92, 477–479. PDF
• Warmenhoven, J., Bargary, N., Liebl, D., Harrison, A. J., Robinson, M. A., Gunning, E. and Hooker, G. (2021). PCA of waveforms and functional PCA: A primer for biomechanics. Journal of Biomechanics, 116, 110106.
• Hollander, K., Liebl, D., Willwacher, S., Meining, S., Mattes, K. and Zech, A. (2019). Adaptation of running biomechanics to repeated barefoot running: A randomized controlled study. The American Journal of Sports Medicine, 47(8), 1975–1983.
• Pataky, T. C., Vanrenterghem, J., Robinson, M. A. and Liebl, D. (2019). On the validity of statistical parametric mapping for nonuniformly and heterogeneously smooth one-dimensional biomechanical data. Journal of Biomechanics, 91, 114–123.
• Hamacher, D., Liebl, D., Hödl, C., Heßler, V., Kniewasser, C. K., Thönnessen, T. and Zech, A. (2019). Gait stability and its influencing factors in older adults. Frontiers in Physiology, 9, 1955.
• Zech, A., Meining, S., Hötting, K., Liebl, D., Mattes, K. and Hollander, K. (2018). Effects of barefoot and footwear conditions on learning of a dynamic balance task: A randomized controlled study. European Journal of Applied Physiology, 118(12), 2699–2706.
• Liebl, D., Willwacher, S., Hamill, J. and Brüggemann, G. P. (2014). Ankle plantarflexion strength in rearfoot and forefoot runners: A novel clusteranalytic approach. Human Movement Science, 35, 104–125. PDF

PhD Thesis

• Liebl, D. (2013). Contributions to functional data analysis with applications to modeling time series and panel data. PhD thesis, University of Cologne.

Open Reviews

• Liebl, D. (2020). Open review of the manuscript An Analysis of SARS-CoV-2 Viral Load by Patient Age by Jones, T. C., Mühlemann, B., Veith, T., Zuchowski, M., Hofmann, J., Stein, A., Edelmann, A., Corman, V. M. and Drosten, C.

Editorial Services

• since 2022Member of the Statistical Advisory Board, Human Movement Science
• 2021–2024Associate Editor, Journal of the Royal Statistical Society: Series C
• 2020–2022Guest Editor, Special Issue: Statistics in Sports, AStA Advances in Statistical Analysis (with Andreas Groll, TU Dortmund University)

Refereeing

• The Annals of Statistics
• Journal of the Royal Statistical Society: Series B
• Journal of the American Statistical Association
• Biometrika
• The Annals of Applied Statistics
• Journal of the Royal Statistical Society: Series C
• Journal of Time Series Analysis
• Computational Statistics & Data Analysis
• Statistical Modelling
• AStA Advances in Statistical Analysis
• Econometrics and Statistics
• Advances in Data Analysis and Classification
• Journal of Computational and Graphical Statistics
• Journal of Applied Statistics
• Energy Economics
• International Journal of Forecasting
• TEST
• Journal of Statistical Planning and Inference
• Journal of Multivariate Analysis
• Statistica Sinica
• Statistics & Probability Letters

Software

R packages accompanying my research papers:

• ffscb — Fast and fair simultaneous confidence bands for functional parameters
• sawr — Wavelet method for panel models with jump discontinuities
• fdapoi — Points of impact in nonparametric regression with functional predictors
• FunRegPoI — Functional linear regression with points of impact
• ReconstPoFD — Optimal reconstruction of partially observed functional data
• PartiallyFD — Partially observed functional data with systematically missing parts
• phtt — Panel data analysis with heterogeneous time trends (with Oualid Bada; creator and maintainer)

Teaching

A selection of past and current courses:

• Computational Statistics / Data Science (B.Sc., M.Sc., PhD), University of Bonn. Statistical learning, regression analysis, classification, resampling methods, linear model selection and regularization, multiple testing, doubly robust machine learning, tree-based methods, functional data analysis.
• Econometrics (M.Sc., PhD), University of Bonn. Probability theory, test theory, multiple linear regression, small- and large-sample inference, maximum likelihood inference, instrumental variable estimation, panel data analysis, time series analysis, causal inference.
• Nonparametric Statistics (B.Sc.), University of Bonn. Rank statistics and tests, nonparametric density estimation, nonparametric hypothesis testing, nonparametric regression.

Miscellaneous

My former life took (mostly) place in dojos, where I used to wear a judogi.