Refereed Publications & Working Papers

2024

[64] Thomas Muschinski, Georg J. Mayr, Thorsten Simon, Nikolaus Umlauf, and Achim Zeileis. Cholesky-based multivariate gaussian regression. Econometrics and Statistics, 29:261–281, 2024. [ bib | DOI ]

[63] Nikolaus Umlauf, Johannes Seiler, Mattias Wetscher, Thorsten Simon, Stefan Lang, and Nadja Klein. Scalable estimation for structured additive distributional regression. Journal of Computational and Graphical Statistics, 0(ja):1–23, 2024. forthcoming. [ bib | DOI ]

[62] Mattias Wetscher, Johannes Seiler, Reto Stauffer, and Nikolaus Umlauf. Stagewise boosting distributional regression. Technical report, 2024. [ bib | DOI ]

[61] Julian Granna, Stefan Lang, and Nikolaus Umlauf. A parsimonious hedonic distributional regression model for large data with heterogeneous covariate effects. Technical report, 2024. [ bib | http ]

[60] Philipp Aschersleben, Julian Granna, Thomas Kneib, Stefan Lang, Nikolaus Umlauf, and Winfried Steiner. Modeling multiplicative interaction effects in gaussian structured additive regression models. Technical report, 2024. [ bib | http ]

[59] Alexander Volkmann, Nikolaus Umlauf, and Sonja Greven. Generalized multivariate functional additive mixed models for location, scale, and shape. Technical report, 2024. [ bib | DOI ]

2023

[58] Alexander Razen, Wolfgang Brunauer, Nadja Klein, Thomas Kneib, Stefan Lang, and Nikolaus Umlauf. A multilevel analysis of real estate valuation using distributional and quantile regression. Statistical Modelling, 2023. [ bib | DOI ]

[57] Thorsten Simon, Georg J. Mayr, Deborah Morgenstern, Nikolaus Umlauf, and Achim Zeileis. Amplification of annual and diurnal cycles of alpine lightning. Climate Dynamics, 2023. [ bib | DOI ]

[56] Mattias Wetscher, Johannes Seiler, Reto Stauffer, and Nikolaus Umlauf. Stagewise boosting distributional regression. In Proceedings of the 37th International Workshop on Statistical Modelling, Dortmund, Germany, 2023. [ bib | http ]

[55] Nikolaus Umlauf, Johannes Seiler, Mattias Wetscher, and Nadja Klein. Boosting distributional soft regression trees. In Proceedings of the 37th International Workshop on Statistical Modelling, Dortmund, Germany, 2023. [ bib | http ]

[54] Nikolaus Umlauf, Johannes Seiler, Mattias Wetscher, Thorsten Simon, Stefan Lang, and Nadja Klein. Scalable estimation for structured additive distributional regression. Technical report, 2023. [ bib | DOI ]

[53] Alexander Volkmann, Nikolaus Umlauf, and Sonja Greven. Flexible joint models for multivariate longitudinal and time-to-event data using multivariate functional principal components. Technical report, 2023. [ bib | DOI ]

2022

[52] Johanna Van Passel, Wanda de Keersmaecker, Paulo N. Bernardino, Xin Jing, Nikolaus Umlauf, Koenraad Van Meerbeek, and Ben Somers. Climatic legacy effects on the drought response of the amazon rainforest. Global Change Biology, 2022. [ bib | DOI ]

[51] Johannes Ingrisch, Nikolaus Umlauf, and Bahn Michael. Functional thresholds alter the relationship of plant resistance and recovery to drought. Ecology, 2022. [ bib | DOI ]

[50] Nikolaus Umlauf and Nadja Klein. Distributional adaptive soft regression trees. Technical report, 2022. [ bib | DOI ]

2021

[49] Nikolaus Umlauf, Nadja Klein, Thorsten Simon, and Achim Zeileis. bamlss: A Lego toolbox for flexible Bayesian regression (and beyond). Journal of Statistical Software, 100(4):1–53, 2021. [ bib | DOI ]

[48] Honey Alas, Almond Stöcker, Nikolaus Umlauf, Oshada Senaweera, Sascha Pfeifer, Sonja Greven, and Alfred Wiedensohler. Pedestrian exposure to black carbon and pm2.5 emissions in urban hot spots: New findings using mobile measurement techniques and flexible Bayesian regression models. Journal of Exposure Science & Environmental Epidemiology, 2021. [ bib | DOI ]

[47] Thorsten Simon, Georg J. Mayr, Deborah Morgenstern, Nikolaus Umlauf, and Achim Zeileis. Amplification of annual and diurnal cycles of alpine lightning. Preprint, Research Square, 2021. [ bib | DOI ]

[46] Thomas Muschinski, Georg J. Mayr, Thorsten Simon, Nikolaus Umlauf, and Achim Zeileis. Cholesky-based multivariate gaussian regression. Technical report, 2021. [ bib | DOI ]

2020

[45] Thorsten Simon and Nikolaus Umlauf. Scaleable distributional regression. In Proceedings of the 35th International Workshop on Statistical Modelling, Bilbao, Spain, 2020. [ bib ]

[44] Lieke Voncken, Thomas Kneib, Casper J Albers, Nikolaus Umlauf, and Marieke Timmerman. Bayesian Gaussian distributional regression models for more efficient norm estimation. British Journal of Mathematical and Statistical Psychology, 74(1):99–117, 2020. [ bib | DOI ]

2019

[43] Thomas Kneib, Nadja Klein, Stefan Lang, and Nikolaus Umlauf. Modular regression - a Lego system for building structured additive distributional regression models with tensor product interactions. TEST, 28(1):1–39, March 2019. [ bib | DOI ]

[42] Thomas Kneib, Nadja Klein, Stefan Lang, and Nikolaus Umlauf. Rejoinder on: Modular regression - a Lego system for building structured additive distributional regression models with tensor product interactions. TEST, 28(1):55–59, March 2019. [ bib | DOI ]

[41] T. Simon, G. J. Mayr, N. Umlauf, and A. Zeileis. NWP-based lightning prediction using flexible count data regression. Advances in Statistical Climatology, Meteorology and Oceanography, 5(1):1–16, 2019. [ bib | DOI ]

[40] Andreas Groll, Julien Hambuckers, Thomas Kneib, and Nikolaus Umlauf. LASSO-type penalization in the framework of generalized additive models for location, scale and shape. Computational Statistics & Data Analysis, 140:59–73, 2019. [ bib | DOI ]

[39] Nadja Klein, Thorsten Simon, and Nikolaus Umlauf. Neural network regression with an application to leukaemia survival data – an unstructured distributional approach. In Proceedings of the 34th International Workshop on Statistical Modelling, Guimarães, Portugal, volume 1, pages 157–160. Statistical Modelling Society, 2019. [ bib ]

[38] Nikolaus Umlauf, Nadja Klein, Thorsten Simon, and Achim Zeileis. bamlss: A Lego toolbox for flexible Bayesian regression (and beyond). arXiv 1909.11784, arXiv.org E-Print Archive, September 2019. [ bib | DOI ]

[37] Lieke Voncken, Thomas Kneib, Casper J Albers, Nikolaus Umlauf, and Marieke Timmerman. Bayesian Gaussian distributional regression models for more efficient norm estimation. Technical report, 2019. [ bib | DOI ]

2018

[36] Nikolaus Umlauf, Nadja Klein, and Achim Zeileis. BAMLSS: Bayesian additive models for location, scale and shape (and beyond). Journal of Computational and Graphical Statistics, 27(3):612–627, 2018. [ bib | DOI ]

[35] Nikolaus Umlauf and Thomas Kneib. A primer on Bayesian distributional regression. Statistical Modelling, 18(3-4):219–247, 2018. [ bib | DOI ]

[34] Janett Kreutziger, Stefan Schmid, Nikolaus Umlauf, Hanno Ulmer, Maarten W. Nijsten, Daniel Werner, Thomas Schlechtriemen, and Wolfgang Lederer. Association between blood glucose and cardiac rhythms during pre-hospital care of trauma patients – a retrospective analysis. Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine, 26(58), 2018. [ bib | DOI ]

[33] Thorsten Simon, Peter Fabsic, Georg J. Mayr, Nikolaus Umlauf, and Achim Zeileis. Probabilistic forecasting of thunderstorms in the eastern Alps. Monthly Weather Review, 146(9):2999–3009, 2018. [ bib | DOI ]

[32] Meike Köhler, Nikolaus Umlauf, and Sonja Greven. Nonlinear association structures in flexible Bayesian additive joint models. Statistics in Medicine, 37(30):4771–4788, 2018. [ bib | DOI ]

[31] Thorsten Simon, Georg J. Mayr, Nikolaus Umlauf, and Achim Zeileis. Lightning prediction using model output statistics. Working papers, Faculty of Economics and Statistics, University of Innsbruck, 2018. [ bib | http ]

[30] Andreas Groll, Julien Hambuckers, Thomas Kneib, and Nikolaus Umlauf. LASSO-type penalization in the framework of generalized additive models for location, scale and shape. Working papers, Faculty of Economics and Statistics, University of Innsbruck, 2018. [ bib | http ]

2017

[29] Meike Köhler, Andreas Beyerlein, Kendra Vehik, Sonja Greven, Nikolaus Umlauf, Åke Lernmark, William A. Hagopian, Marian Rewers, Jin-Xiong She, Jorma Toppari, Beena Akolkar, Jeffrey P. Krischer, Ezio Bonifacio, and Anette-G. Ziegler. Joint modeling of longitudinal autoantibody patterns and progression to type 1 diabetes: Results from the teddy study. Acta Diabetologica, 54(11):1009–1017, November 2017. [ bib | DOI ]

[28] Reto Stauffer, Georg J. Mayr, Jakob W. Messner, Nikolaus Umlauf, and Achim Zeileis. Spatio-temporal precipitation climatology over complex terrain using a censored additive regression model. International Journal of Climatology, 37(7):3264–3275, 2017. [ bib | DOI ]

[27] Reto Stauffer, Nikolaus Umlauf, Jakob W. Messner, Georg J. Mayr, and Achim Zeileis. Ensemble postprocessing of daily precipitation sums over complex terrain using censored high-resolution standardized anomalies. Monthly Weather Review, 145(3):955–969, 2017. [ bib | DOI ]

[26] T. Simon, N. Umlauf, A. Zeileis, G. J. Mayr, W. Schulz, and G. Diendorfer. Spatio-temporal modelling of lightning climatologies for complex terrain. Natural Hazards and Earth System Sciences, 17(3):305–314, 2017. [ bib | DOI ]

[25] Meike Köhler, Nikolaus Umlauf, Andreas Beyerlein, Christiane Winkler, Anette-Gabriele Ziegler, and Sonja Greven. Flexible Bayesian additive joint models with an application to type 1 diabetes research. Biometrical Journal, 59(6):1144–1165, 2017. [ bib | DOI ]

[24] Thorsten Simon, Nikolaus Umlauf, Georg J. Mayr, and Achim Zeileis. Boosting multivariate Gaussian models for probabilistic temperature forecasts. In Proceedings of the 32nd International Workshop on Statistical Modelling, Groningen, Netherlands, pages 143–148. University of Groningen, 2017. [ bib ]

[23] Andreas Groll, Thomas Kneib, and Nikolaus Umlauf. Lasso-type penalization in the framework of generalized additive models for location scale and shape. In Proceedings of the 32nd International Workshop on Statistical Modelling, Groningen, Netherlands, pages 103–108. University of Groningen, 2017. [ bib ]

[22] Thomas Kneib and Nikolaus Umlauf. A primer on Bayesian distributional regression. Working Paper 2017-13, Working Papers in Economics and Statistics, Research Platform Empirical and Experimental Economics, Universität Innsbruck, August 2017. [ bib | http ]

[21] Nikolaus Umlauf, Nadja Klein, and Achim Zeileis. BAMLSS: Bayesian additive models for location, scale and shape (and beyond). Working Paper 2017-05, Working Papers in Economics and Statistics, Research Platform Empirical and Experimental Economics, Universität Innsbruck, February 2017. [ bib | http ]

[20] Thomas Kneib, Nadja Klein, Stefan Lang, and Nikolaus Umlauf. Modular regression - a Lego system for building structured additive distributional regression models with tensor product interactions. Technical report, 2017. [ bib ]

[19] Meike Köhler, Nikolaus Umlauf, and Sonja Greven. Nonlinear association structures in flexible Bayesian additive joint models, 2017. [ bib | arXiv ]

[18] Thorsten Simon, Peter Fabsic, Georg J. Mayr, Nikolaus Umlauf, and Achim Zeileis. Probabilistic forecasting of thunderstorms in the eastern Alps. Working papers, Faculty of Economics and Statistics, University of Innsbruck, 2017. [ bib | http ]

2016

[17] Jan Verbesselt, Nikolaus Umlauf, Marina Hirota, Milena Holmgren, Egbert H. Van Nes, Martin Herold, Achim Zeileis, and Marten Scheffer. Remotely sensed resilience of tropical forests. Nature Clim. Change, advance online publication, September 2016. Letter. [ bib | DOI ]

[16] Reto Stauffer, Jakob W. Messner, Georg J. Mayr, Nikolaus Umlauf, and Achim Zeileis. Spatio-temporal precipitation climatology over complex terrain using a censored additive regression model. Working papers, Faculty of Economics and Statistics, University of Innsbruck, 2016. [ bib | http ]

[15] T. Simon, N. Umlauf, A. Zeileis, G. J. Mayr, W. Schulz, and G. Diendorfer. Spatio-temporal smoothing of lightning climatologies. Natural Hazards and Earth System Sciences Discussions, 2016:1–15, 2016. [ bib | DOI ]

[14] Meike Köhler, Nikolaus Umlauf, Andreas Beyerlein, Christiane Winkler, Anette-Gabriele Ziegler, and Sonja Greven. Flexible Bayesian additive joint models with an application to type 1 diabetes research, 2016. [ bib | arXiv ]

2015

[13] Nikolaus Umlauf, Daniel Adler, Thomas Kneib, Stefan Lang, and Achim Zeileis. Structured additive regression models: An R interface to Bayesx. Journal of Statistical Software, 63(21):1–46, 2015. [ bib | DOI ]

[12] Alexander Razen, Wolfgang Brunauer, Nadja Klein, Stefan Lang, and Nikolaus Umlauf. Hedonic house price modeling based on multilevel structured additive regression. In M. Helbich, J. Jokar, and M Leitner, editors, Computational Approaches for Urban Economics. Springer Verlag, 2015. [ bib | http ]

[11] Nikolaus Umlauf, Reto Stauffer, Jakob Messner, Georg Mayr, and Achim Zeileis. A conceptional Lego toolbox for Bayesian distributional regression models. In Proceedings of the 30th International Workshop on Statistical Modelling, Linz, Austria. JKU Linz, 2015. [ bib | .pdf ]

2014

[10] Achim Zeileis, Nikolaus Umlauf, and Friedrich Leisch. Flexible generation of e-learning exams in r: Moodle quizzes, olat assessments, and beyond. Journal of Statistical Software, 58(1):1–36, 2014. [ bib | DOI ]

[9] Alexander Razen, Wolfgang Brunauer, Nadja Klein, Thomas Kneib, Stefan Lang, and Nikolaus Umlauf. Statistical risk analysis for real estate collateral valuation using Bayesian distributional and quantile regression. Working Paper 2014-12, Working Papers in Economics and Statistics, Research Platform Empirical and Experimental Economics, Universität Innsbruck, April 2014. [ bib | http ]

2013

[8] Michael Ess, Katja Heitmair-Wietzorrek, Matthias Frick, Nikolaus Umlauf, Hanno Ulmer, and Gerhard Poelzl. Serum phosphate and long-term outcome among patients with stable heart failure. Journal of Cardiac Failure, 19(1):25–30, 2013. [ bib | http ]

[7] Wolfgang Brunauer, Stefan Lang, and Nikolaus Umlauf. Modeling house prices using multilevel structured additive regression. Statistical Modelling, 13:95–123, 2013. [ bib | http ]

2012

[6] Nikolaus Umlauf, Georg Mayr, Jakob Messner, and Achim Zeileis. Why does it always rain on me? A spatio-temporal analysis of precipitation in Austria. Austrian Journal of Statistics, 41(1):81–92, 2012. [ bib | DOI ]

[5] Stefan Lang, Nikolaus Umlauf, Peter Wechselberger, Kenneth Harttgen, and Thomas Kneib. Multilevel structured additive regression. Statistics and Computing, 24(2):223–238, 2012. [ bib | DOI ]

[4] Achim Zeileis, Nikolaus Umlauf, and Friedrich Leisch. Flexible generation of e-learning exams in R: Moodle quizzes, olat assessments, and beyond. Working Paper 2012-27, Working Papers in Economics and Statistics, Research Platform Empirical and Experimental Economics, Universität Innsbruck, December 2012. [ bib | http ]

[3] Stefan Lang, Nikolaus Umlauf, Peter Wechselberger, Kenneth Harttgen, and Thomas Kneib. Multilevel structured additive regression. Working Paper 2012-07, Working Papers in Economics and Statistics, Research Platform Empirical and Experimental Economics, Universität Innsbruck, April 2012. [ bib | http ]

2011

[2] Alexander M. Strasak, Nikolaus Umlauf, Ruth M. Pfeiffer, and Stefan Lang. Comparing penalized splines and fractional polynomials as smoothing techniques for flexible modelling the effect of continuous predictor variables. Computational Statistics & Data Analysis, 55:1540–1551, 2011. [ bib | DOI ]

2010

[1] Stefan Lang, Nikolaus Umlauf, and Wolfgang Brunauer. Hierarchical structured additive regression. In Adrian Bowman, editor, Proceedings of the 25th International Workshop on Statistical Modelling, Glasgow, Scotland, UK. Glasgow University Print Unit, 2010. [ bib ]