Welcome
… to my website. I am an Associate Professor of Statistics at the University of Bonn.

I pursue an application oriented research approach focusing on actual real data problems that are both statistically interesting and practically relevant. Starting points of my past and current research are data challenges in (energy) economics, finance, e-commerce (e.g., Google AdWords data), emotion psychology, biomechanics, and human movement sciences.

My current methodological and theoretical research interests focus on functional data analysis, nonparametric statistics, longitudinal data analysis, simultaneous inference, and statistical fairness. Last but not least, I am committed to providing the computational implementations of my statistical research and publish R-packages at CRAN and GitHub accompanying my research papers.

Bio

Publications

Publications in Statistics

Book Chapters

  • Liebl, D. and Reimherr, M. (2020). Simultaneous Inference for Function-valued Parameters: a Fast and Fair Approach. Functional and High-Dimensional Statistics and Related Fields. Edited by: Aneiros, G., Horová, I., Hužková, M. and Vieu, P., pp. 153-159

  • Walders, F. and Liebl, D. (2017). Parameter regimes in partially functional linear regression for panel data. Functional Statistics and Related Fields. Edited by: Aneiros, G., Bongiorno, E. G., Cao, R., Vieu, P., pp. 261-270

  • Liebl, D. and Kneip, A. (2014). Modelling electricity prices as functional data on random domains. Contributions in Infinite-Dimensional Statistics and Related Topics. Edited by: Bongiorno, E. G., Salinelli, E., Goia, A., Vieu, P., pp. 90-97

  • Liebl, D., Mosler, K. and Willwacher, S. (2012). Robust clustering of joint moment curves. 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., Woll, A., pp. 68-73

Further Publications

PhD Thesis

Open Reviews

Working Papers

Work in Progress

  • Bada, O. and Liebl, D. A subsampled penalty criterion to estimate the number of non-vanishing common factors in large panels

  • Liebl, D. On the minor role of bandwidth selection when smoothing sparse to dense functional data

  • Liebl, D. and Rust, C. Directed local testing in the functional linear model

  • Gider, J. and Liebl, D. Observe the unobservable: Firm value and firm-specific heterogeneity in time trends

  • Liebl, D. and Mensinger, T. Fair causal inference with functional data

  • Hörmann, S., Kraus, D., and Liebl, D. Testing the MCAR-assumption for partially observed functional data

Editorial Services

Refereeing

The Annals of Statistics (AOS), Journal of the Royal Statistical Society: Series B (JRSSB), Journal of the American Statistical Association (JASA), Biometrika, The Annals of Applied Statistics (AOAS), Journal of the Royal Statistical Society: Series C (JRSSC), Journal of Time Series Analysis (JTSA), Computational Statistics & Data Analysis (CSDA), Statistical Modeling: An International Journal (SMIJ), Advances in Statistical Analysis (AStA), Econometrics and Statistics (ECOSTA), Advances in Data Analysis and Classification (ADAC), Journal of Computational and Graphical Statistics (JCGS), Journal of Applied Statistics (JAS), Energy Economics (ENEECO), International Journal of Forecasting (IJF), TEST: Journal of the Spanish Society of Statistics and Operations Research, Journal of Statistical Planning and Inference (JSPI), Journal of Multivariate Analysis (JMVA), Statistica Sinica (SS), Statistics and Probability Letters (STAPRO)

Software

  • Together with my co-author Oualid Bada, I am the creator and maintainer of the R-package phtt. The package provides estimation procedures for panel data with general forms of unobservable heterogeneous effects.

  • R-package FunRegPoI

  • R-package PartiallyFD

  • R-package ReconstPoFD

  • R-package fdapoi

  • R-package sawr

  • R-package ffscb

Teaching Portfolio

Excerpt of past and current courses:

  • Computational Statistics/Data Science (M.Sc., B.Sc., and PhD) at the University Bonn
    Main Textbook: Introduction to Statistical Learning. Contents: Statistical Learning, Regression Analysis, Classification, Resampling Methods, Linear Model Selection and Regularization, Multiple testing, Tree-Based Methods, Functional Data Analysis, Fairness

  • The beginnings of a lecture script for Computational Statistics (fun side project in German): Online Skrip (German)

  • Short lecture A Gentle Introduction to Functional Data Analysis at the University of Passau
    Main Textbook: Introduction to Functional Data Analysis by Kokoszka, P., and Reimherr, M.
    Course Material

  • Econometrics (M.Sc. and PhD) at the University of Bonn. Contents: 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.) at the University of Bonn
    Main Textbooks: Nichtparametrische Statistische Methoden by Büning, H., Trenkler, G., and
    Local Polynomial Modelling and its Applications by Fan, J. and Gijbels, I. Contents: Test Theory, Linear Rank Statistics, Introduction to Mathematical Statistics, Kernel Density Estimation, Nonparametric Regression Analysis


Fundings & Affiliations

Miscellaneous

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