Heidi Seibold
Cited by
Cited by
Model-Based Recursive Partitioning for Subgroup Analyses
H Seibold, A Zeileis, T Hothorn
The international journal of biostatistics 12 (1), 45-63, 2016
Invertebrates outcompete vertebrate facultative scavengers in simulated lynx kills in the Bavarian Forest National Park, Germany
RR Ray, H Seibold, M Heurich
Animal Biodiversity and Conservation 37 (1), 77-88, 2014
Individual treatment effect prediction for amyotrophic lateral sclerosis patients
H Seibold, A Zeileis, T Hothorn
Statistical methods in medical research 27 (10), 3104-3125, 2018
OpenML: An R package to connect to the machine learning platform OpenML
G Casalicchio, J Bossek, M Lang, D Kirchhoff, P Kerschke, B Hofner, ...
Computational Statistics 34 (3), 977-991, 2019
Patterns of lynx predation at the interface between protected areas and multi-use landscapes in central Europe
E Belotti, N Weder, L Bufka, A Kaldhusdal, H Küchenhoff, H Seibold, ...
PloS one 10 (9), e0138139, 2015
On the choice and influence of the number of boosting steps for high-dimensional linear Cox-models
H Seibold, C Bernau, AL Boulesteix, R De Bin
Computational Statistics, 1-21, 2018
Generalised linear model trees with global additive effects
H Seibold, T Hothorn, A Zeileis
Advances in Data Analysis and Classification 13 (3), 703-725, 2019
Subgroup identification in dose‐finding trials via model‐based recursive partitioning
M Thomas, B Bornkamp, H Seibold
Statistics in medicine 37 (10), 1608-1624, 2018
Subgroup identification in clinical trials: an overview of available methods and their implementations with R
Z Zhang, H Seibold, MV Vettore, WJ Song, V François
Annals of Translational Medicine 6 (7), 2018
Survival forests under test: Impact of the proportional hazards assumption on prognostic and predictive forests for amyotrophic lateral sclerosis survival
N Korepanova, H Seibold, V Steffen, T Hothorn
Statistical Methods in Medical Research 29 (5), 1403-1419, 2020
Estimating patient-specific treatment advantages in the ‘Treatment for Adolescents with Depression Study’
S Foster, M Mohler-Kuo, L Tay, T Hothorn, H Seibold
Journal of psychiatric research 112, 61-70, 2019
Open Science in Software Engineering
D Méndez Fernández, D Graziotin, S Wagner, H Seibold
arXiv, arXiv: 1904.06499, 2019
model4you: An R Package for Personalised Treatment Effect Estimation
H Seibold, A Zeileis, T Hothorn
Journal of Open Research Software 7 (1), 2019
OpenML: An R package to connect to the networked machine learning platform OpenML
G Casalicchio, J Bossek, M Lang, D Kirchhoff, P Kerschke, B Hofner, ...
stat 1050, 5, 2017
Distributional Regression Forests for Probabilistic Modeling and Forecasting
L Schlosser, T Hothorn, H Seibold, A Zeileis
Universität Innsbruck.(International R User 2017 Conference Presentation), 2017
An environment for sustainable research software in Germany and beyond: current state, open challenges, and call for action
H Anzt, F Bach, S Druskat, F Löffler, A Loewe, BY Renard, G Seemann, ...
arXiv preprint arXiv:2005.01469, 2020
de-RSE-The German RSE Chapter
H Seibold, S Janosch
Open Science Days 2019, 2019
Package ‘highriskzone’
H Seibold, M Mahling, MH Seibold, I Suggests
Model-based recursive partitioning for stratified and personalised medicine
H Seibold
University of Zurich, 2018
Distributional Trees and Forests
L Schlosser, T Hothorn, H Seibold, A Zeileis
The R User Conference, useR! 2017 July 4-7 2017 Brussels, Belgium, 95, 2017
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