Heidi Seibold
Heidi Seibold
Department of Statistics, LMU
Verified email at stat.uni-muenchen.de - Homepage
Title
Cited by
Cited by
Year
Model-Based Recursive Partitioning for Subgroup Analyses
H Seibold, A Zeileis, T Hothorn
The international journal of biostatistics 12 (1), 45-63, 2016
722016
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, 1-15, 2017
292017
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
282014
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
252018
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), 2015
182015
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
102019
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
92018
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
92018
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
62018
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
52019
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
42020
Survival Forests under Test: Impact of the Proportional Hazards Assumption on Prognostic and Predictive Forests for ALS Survival
N Korepanova, H Seibold, V Steffen, T Hothorn
arXiv preprint arXiv:1902.01587, 2019
4*2019
On the choice and influence of the number of boosting steps
H Seibold, C Bernau, AL Boulesteix, R De Bin
42016
Open Science in Software Engineering
DM Fernández, D Graziotin, S Wagner, H Seibold
arXiv preprint arXiv:1904.06499, 2019
32019
Open Science in Software Engineering
D Mendez, D Graziotin, S Wagner, H Seibold
arXiv preprint arXiv:1904.06499, 2019
32019
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
22017
model4you: An R Package for Personalised Treatment Effect Estimation
H Seibold, A Zeileis, T Hothorn
Journal of Open Research Software 7 (1), 2019
12019
Open Science in Software Engineering
D Méndez Fernández, D Graziotin, S Wagner, H Seibold
arXiv preprint arXiv:1904.06499, 2019
12019
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
12017
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
2020
The system can't perform the operation now. Try again later.
Articles 1–20