Research

Publications

  • Döhler, S., Meah, I., and Roquain, E. (2024), Online multiple testing with super-uniformity reward, Electronic Journal of Statistics, publication, Volume 18, Number 1, 1293-1354. 
  • Döhler, S. and Meah, I. (2023),  A unified class of null proportion estimators with plug-in fdr control, preprint (arXiv) 
  • Cousido-Rocha, M., Döhler, S. and de Una-Alvarez, J. (2022), Multiple comparison procedures for discrete uniform and homogeneous tests, Journal of the Royal Statistical Society: Series C (Applied Statistics), Number 2, 4244-4272.
  • Döhler, S. and Roquain, E. (2020), Controlling the false discovery exceedance for heterogeneous tests , Electronic Journal of Statistics, publication, Volume 14, Number 2, 4244-4272. (R package FDX)
  • Döhler, S., Martin, M.R.W., Gies, J. and Troll, M. (2019), RASBOP: Ranking and Selection-Methods for the  Backtest-Overfitting-Problem, tech. report (available on request) 
  • Durand, G., Junge, F., Döhler, S., and Roquain, E. (2019), DiscreteFDR: An R package for controlling the false discovery rate for discrete test statistics, preprint (arXiv)
  • Döhler, S., Durand, G. and Roquain, E. (2018), New FDR bounds for discrete and heterogeneous tests, Electronic Journal of Statistics, publication, Volume 12, Number 1 , 1867-1900 (R package DiscreteFDR)
  • Döhler, S. (2018), A discrete modification of the Benjamini-Yekutieli procedure, Econometrics and Statistics, preprint (arXiv), vol 5, p. 137-147;
    https://www.sciencedirect.com/science/article/abs/pii/S2452306216300351
  • Castro-Conde, I., Döhler, S. and de Una-Alvarez, J. (2015), An extended sequential goodness-of-fit multiple testing method for discrete data, Statistical Methods in Medical Research, journals.sagepub.com/doi/full/10.1177/0962280215597580 , R-package SGoF
  • Döhler, S. (2014), A sufficient criterion for control of some generalized error rates in multiple testing,
    Statistics and Probability Letters, 92(2014), p.114-120, www.sciencedirect.com/science/article/pii/S0167715214001850
  • Cottin, C. and Döhler, S. (2013), Risikoanalyse, zweite überarbeitete und erweiterte Auflage, Springer Spektrum Verlag (Homepage bei Springer)
  • Döhler, S. (2010), Validation of credit default probabilities using multiple-testing procedures,
    Journal of Risk Model Validation, 4, No. 4, 2010, 59–92 (preprint,article)
  • Cottin, C. and Döhler, S. (2009), Risikoanalyse, Vieweg+Teubner
  • Döhler, S. and Rüschendorf, L. (2003), Nonparametric estimation of regression functions in point process models,
    Statistical Inference for Stochastic Processes, 6, No. 3, 2003, 291-307 (pdf)
  • Döhler, S. and Rüschendorf, L. (2003), A consistency result in general censoring models,
    Statistics, 37, No. 3, 2003, 205-216
  • Döhler, S. and Rüschendorf, L. (2002), On adaptive estimation by neural net type estimators,
    in: Nonlinear Estimation and Classification, D. Denison, M. Hansen, C. Holmes, B. Mallick, B. Yu (Eds.), Lecture Notes in Statistics, 171, 2002, 381-392
  • Döhler, S. and Rüschendorf, L. (2002), Adaptive estimation of hazard functions,
    Probability and Mathematical Statistics, 22, 2002, 355-379 (pdf)
  • Döhler, S. (2002) Consistent hazard regression estimation by sieved maximum likelihood estimators,
    in: Limit Theorems in Probability and Statistics, Balatonlelle 1999, I. Berkes, E. Csaki, M. Csörgö (Eds.), 2002, 553-569
  • Döhler, S. and Rüschendorf, L. (2001), An approximation result for nets in functional estimation,
    Statistics and Probability Letters, 52, 2001, 373-380 (pdf)
  • Döhler, S. (2000), Empirische Risikominimierung bei zensierten Daten,
    Dissertation, Universität Freiburg, 2000

Software

  • Junge, F., Döhler, S. and Roquain, E. (2020), FDX: False Discovery Exceedance Controlling Multiple Testing Procedures, R package
  • Durand, G., Junge, F., Döhler, S. and Roquain, E. (2018), DiscreteFDR: Multiple Testing Procedures with Adaptation for Discrete Tests, R package, R vignette

Talks

  • Online multiple testing with super-uniformity reward, CMStatistics 2023 Conference, Berlin, 2023
  • Controlling the False Discovery Exceedance for Heterogeneous Tests, DAGStat 2022, Hamburg, 2022
  • Invited discussant of Empirical Bayes Control of the False Discovery Exceedance (by Pallavi Basu et al.), International Seminar on Selective Inference, 2021
  • Controlling the False Discovery Exceedance for discrete tests, The 11th International Conference on Multiple Comparison Procedures,Taipeh, Taiwan, 2019
  • Controlling the false discovery rate for discrete test statistics: Some results and computational tools, Biometrisches Kolloquium der Medizinischen Universität Wien, 2019
  • DiscreteFDR: An R-package for controlling the false discovery rate for discrete test statistics, DAGStat 2019, München, 2019
  • DiscreteFDR: An R-package for controlling the false discovery rate for discrete tests, 11th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2018), Pisa
  • Controlling the false discovery rate for discrete data: New results and computational tools, 23rd International Conference on Computational Statistics, Iasi, Rumänien
  • New false discovery rate controlling procedures for discrete data, Stochastisches Kolloquium, Goethe-University Frankfurt, 2017
  • New procedures for discrete tests with proven FDR control, Conference on Multiple Comparison Procedures, UC Riverside, USA, 2017
  • An introductory course on multiple comparison procedures, Universität Vigo, Spanien, 2017
  • False discovery rate procedures for discrete data, Stochastic Models, Statistics and Their Applications, Humboldt-Universität Berlin, 2017
  • A modified Benjamini-Hochberg procedure for discrete data, 9th International Conference of the ERCIM WG on Computational and Methodological Statistics, Sevilla, Spanien, 2016
  • Improving the Power of the Benjamini-Hochberg Procedure for Discrete Data, Joint Statistical Meetings, Chicago, USA, 2016
  • Controlling the false discovery rate for discrete data, Workshop on Recent Developments in Finance, Risk Theory and Stochastic Analysis in honor of Ludger Rüschendorf, Freiburg University, 2016
  • A discrete modification of the Benjamini-Hochberg procedure using a weighting approach, 8th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2015), University of London, UK
  • Some step-up procedures that control the false discovery rate for discrete tests, Vigo University, Spain, 2015
  • Some step-up procedures that control the false discovery rate for discrete tests, 7th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2014), University of Pisa, Italy
  • Controlling generalised error rates, Vigo University, Spain, 2013
  • A sufficient criterion for control of generalised error rates in multiple testing, 8th International Conference on Multiple Comparison Procedures, 2013, University of Southampton, UK
  • Some improvements for multiple testing procedures that control generalised error rates under arbitrary dependence, 3rd joint Statistical Meeting DAGStat, 2013, University of Freiburg
  • Some improvements for multiple testing procedures that control generalised error rates, German Probability and Statistics days 2012, University of Mainz
  • Validation of credit default probabilities via multiple testing procedures, Prague Stochastics 2010, Prague University, Czech Republic