239 citations · 1k across the 28 of their papers we have counts for
29 papers
Refuting "Debunking the GAMLSS Myth: Simplicity Reigns in Pulmonary Function Diagnostics"
Robert A. Rigby, Mikis D. Stasinopoulos, Achim Zeileis +7
We read with interest the above article by Zavorsky (2025, Respiratory Medicine, doi:10.1016/j.rmed.2024.107836) concerning reference equations for pulmonary function testing. The…
colorspace: A Python Toolbox for Manipulating and Assessing Colors and Palettes
Reto Stauffer, Achim Zeileis
The Python colorspace package provides a toolbox for mapping between different color spaces which can then be used to generate a wide range of perceptually-based color palettes for…
Long-term foehn reconstruction combining unsupervised and supervised learning
Reto Stauffer, Achim Zeileis, Georg J. Mayr
Foehn winds, characterized by abrupt temperature increases and wind speed changes, significantly impact regions on the leeward side of mountain ranges, e.g., by spreading wildfires…
Spatio-seasonal risk assessment of upward lightning at tall objects using meteorological reanalysis data
Isabell Stucke, Deborah Morgenstern, Georg J. Mayr +5
This study investigates lightning at tall objects and evaluates the risk of upward lightning (UL) over the eastern Alps and its surrounding areas. While uncommon, UL poses a threat…
Subgroup detection in linear growth curve models with generalized linear mixed model (GLMM) trees
Marjolein Fokkema, Achim Zeileis
Growth curve models are popular tools for studying the development of a response variable within subjects over time. Heterogeneity between subjects is common in such models, and re…
Tree models for assessing covariate-dependent method agreement
Siranush Karapetyan, Achim Zeileis, André Henriksen +1
Method comparison studies explore the agreement of measurements made by two or more methods. Commonly, agreement is evaluated by the well-established Bland-Altman analysis. However…
CRAN Task Views: The Next Generation
Achim Zeileis, Roger Bivand, Dirk Eddelbuettel +2
CRAN Task Views have been available on the Comprehensive R Archive Network since 2005. They provide guidance about which CRAN packages are relevant for tasks related to a certain t…
Coloring in R's Blind Spot
Achim Zeileis, Paul Murrell
Prior to version 4.0.0 R had a poor default color palette (using highly saturated red, green, blue, etc.) and provided very few alternative palettes, most of which also had poor pe…
Upward lightning at wind turbines: Risk assessment from larger-scale meteorology
Isabell Stucke, Deborah Morgenstern, Thorsten Simon +5
Upward lightning (UL) has become an increasingly important threat to wind turbines as ever more of them are being installed for renewably producing electricity. The taller the wind…
What Makes Forest-Based Heterogeneous Treatment Effect Estimators Work?
Susanne Dandl, Torsten Hothorn, Heidi Seibold +3
Estimation of heterogeneous treatment effects (HTE) is of prime importance in many disciplines, ranging from personalized medicine to economics among many others. Random forests ha…
Upward Lightning at the Gaisberg Tower: Initiation Mechanism and Flash Type and the Atmospheric Influence
Isabell Stucke, Deborah Morgenstern, Gerhard Diendorfer +5
Upward lightning is much rarer than downward lightning and requires tall (~m) structures to initiate. It may be either triggered by other lightning discharges or completely s…
Hybrid Machine Learning Forecasts for the UEFA EURO 2020
Andreas Groll, Lars Magnus Hvattum, Christophe Ley +4
Three state-of-the-art statistical ranking methods for forecasting football matches are combined with several other predictors in a hybrid machine learning model. Namely an ability…
Cholesky-based multivariate Gaussian regression
Thomas Muschinski, Georg J. Mayr, Thorsten Simon +2
Distributional regression is extended to Gaussian response vectors of dimension greater than two by parameterizing the covariance matrix of the response distribution using the…
Bias Reduction as a Remedy to the Consequences of Infinite Estimates in Poisson and Tobit Regression
Susanne Köll, Ioannis Kosmidis, Christian Kleiber +1
Data separation is a well-studied phenomenon that can cause problems in the estimation and inference from binary response models. Complete or quasi-complete separation occurs when…
Circular Regression Trees and Forests with an Application to Probabilistic Wind Direction Forecasting
Moritz N. Lang, Lisa Schlosser, Torsten Hothorn +3
While circular data occur in a wide range of scientific fields, the methodology for distributional modeling and probabilistic forecasting of circular response variables is rather l…
bamlss: A Lego Toolbox for Flexible Bayesian Regression (and Beyond)
Nikolaus Umlauf, Nadja Klein, Thorsten Simon +1
Over the last decades, the challenges in applied regression and in predictive modeling have been changing considerably: (1) More flexible model specifications are needed as big(ger…
The Power of Unbiased Recursive Partitioning: A Unifying View of CTree, MOB, and GUIDE
Lisa Schlosser, Torsten Hothorn, Achim Zeileis
A core step of every algorithm for learning regression trees is the selection of the best splitting variable from the available covariates and the corresponding split point. Early…
Hybrid Machine Learning Forecasts for the FIFA Women's World Cup 2019
Andreas Groll, Christophe Ley, Gunther Schauberger +2
In this work, we combine two different ranking methods together with several other predictors in a joint random forest approach for the scores of soccer matches. The first ranking…
Bivariate Gaussian models for wind vectors in a distributional regression framework
Moritz N. Lang, Georg J. Mayr, Reto Stauffer +1
A new probabilistic post-processing method for wind vectors is presented in a distributional regression framework employing the bivariate Gaussian distribution. In contrast to prev…
colorspace: A Toolbox for Manipulating and Assessing Colors and Palettes
Achim Zeileis, Jason C. Fisher, Kurt Hornik +5
The R package colorspace provides a flexible toolbox for selecting individual colors or color palettes, manipulating these colors, and employing them in statistical graphics and da…
Massively-Parallel Break Detection for Satellite Data
Malte von Mehren, Fabian Gieseke, Jan Verbesselt +3
The field of remote sensing is nowadays faced with huge amounts of data. While this offers a variety of exciting research opportunities, it also yields significant challenges regar…
Distributional Regression Forests for Probabilistic Precipitation Forecasting in Complex Terrain
Lisa Schlosser, Torsten Hothorn, Reto Stauffer +1
To obtain a probabilistic model for a dependent variable based on some set of explanatory variables, a distributional approach is often adopted where the parameters of the distribu…
Transformation Forests
Torsten Hothorn, Achim Zeileis
Regression models for supervised learning problems with a continuous target are commonly understood as models for the conditional mean of the target given predictors. This notion i…
Generalised Linear Model Trees with Global Additive Effects
Heidi Seibold, Torsten Hothorn, Achim Zeileis
Model-based trees are used to find subgroups in data which differ with respect to model parameters. In some applications it is natural to keep some parameters fixed globally for al…