References in zbMATH (referenced in 15 articles , 1 standard article )

Showing results 1 to 15 of 15.
Sorted by year (citations)

  1. Stöcker, Almond; Brockhaus, Sarah; Schaffer, Sophia Anna; von Bronk, Benedikt; Opitz, Madeleine; Greven, Sonja: Boosting functional response models for location, scale and shape with an application to bacterial competition (2021)
  2. Umlauf, N., Klein, N., Simon, T., Zeileis, A: bamlss: A Lego Toolbox for Flexible Bayesian Regression (and Beyond) (2021) not zbMATH
  3. Groll, Andreas; Hambuckers, Julien; Kneib, Thomas; Umlauf, Nikolaus: LASSO-type penalization in the framework of generalized additive models for location, scale and shape (2019)
  4. Schlosser, Lisa; Hothorn, Torsten; Stauffer, Reto; Zeileis, Achim: Distributional regression forests for probabilistic precipitation forecasting in complex terrain (2019)
  5. Hothorn, Torsten; Möst, Lisa; Bühlmann, Peter: Most likely transformations (2018)
  6. Mayr, Andreas; Hofner, Benjamin: Boosting for statistical modelling-a non-technical introduction (2018)
  7. Ötting, Marius; Langrock, Roland; Deutscher, Christian: Integrating multiple data sources in match-fixing warning systems (2018)
  8. Schauberger, Gunther; Groll, Andreas: Predicting matches in international football tournaments with random forests (2018)
  9. Thomas, Janek; Mayr, Andreas; Bischl, Bernd; Schmid, Matthias; Smith, Adam; Hofner, Benjamin: Gradient boosting for distributional regression: faster tuning and improved variable selection via noncyclical updates (2018)
  10. Waldmann, Elisabeth: Quantile regression: a short story on how and why (2018)
  11. Greven, Sonja; Scheipl, Fabian: A general framework for functional regression modelling (2017)
  12. Mayr, Andreas; Hofner, Benjamin; Waldmann, Elisabeth; Hepp, Tobias; Meyer, Sebastian; Gefeller, Olaf: An update on statistical boosting in biomedicine (2017)
  13. Hofner, Benjamin; Kneib, Thomas; Hothorn, Torsten: A unified framework of constrained regression (2016)
  14. Benjamin Hofner, Andreas Mayr, Matthias Schmid: gamboostLSS: An R Package for Model Building and Variable Selection in the GAMLSS Framework (2014) arXiv
  15. Kneib, Thomas: Beyond mean regression (2013)