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Veröffentlichungsdatum
Anzahl der Publikationen: 18
2018
Mayr, Andreas und Hofner, Benjamin
(2018):
Boosting for statistical modelling: A non-technical introduction.
In: Statistical Modelling, Bd. 18, Nr. 3-4: S. 365-384
[PDF, 1MB]
Groll, Andreas; Kneib, Thomas; Mayr, Andreas und Schauberger, Gunther
(2018):
On the dependency of soccer scores - a sparse bivariate Poisson model for the UEFA European football championship 2016.
In: Journal of Quantitative Analysis in Sports, Bd. 14, Nr. 2: S. 65-79
Thomas, Janek; Mayr, Andreas; Bischl, Bernd; Schmid, Matthias; Smith, Adam und Hofner, Benjamin
(2018):
Gradient boosting for distributional regression: faster tuning and improved variable selection via noncyclical updates.
In: Statistics and Computing, Bd. 28, Nr. 3: S. 673-687
Brockhaus, Sarah; Fuest, Andreas; Mayr, Andreas und Greven, Sonja
(2018):
Signal regression models for location, scale and shape with an application to stock returns.
In: Journal of the Royal Statistical Society Series C-Applied Statistics, Bd. 67, Nr. 3: S. 665-686
2017
Thomas, Janek; Hepp, Tobias; Mayr, Andreas und Bischl, Bernd
(2017):
Probing for Sparse and Fast Variable Selection with Model-Based Boosting.
In: Computational and Mathematical Methods in Medicine, Bd. 2017, 1421409
[PDF, 1MB]
Mayr, Andreas; Hofner, Benjamin; Waldmann, Elisabeth; Hepp, Tobias; Meyer, Sebastian und Gefeller, Olaf
(2017):
An Update on Statistical Boosting in Biomedicine.
In: Computational and Mathematical Methods in Medicine, Bd. 2017, 6083072
[PDF, 528kB]
Gefeller, Olaf; Hofner, Benjamin; Mayr, Andreas und Waldmann, Elisabeth
(2017):
Predictive Modelling Based on Statistical Learning in Biomedicine.
In: Computational and Mathematical Methods in Medicine, Bd. 2017, 4041736
[PDF, 282kB]
2016
Groll, Andreas; Kneib, Thomas; Mayr, Andreas und Schauberger, Gunther
(22. Juli 2016):
Who’s the Favourite? – A Bivariate Poisson Model for the UEFA European Football Championship 2016.
Department of Statistics: Technical Reports, Nr. 195
[PDF, 588kB]
2014
Mayr, Andreas und Schmid, Matthias
(2014):
Boosting the concordance index for survival data - a unified framework to derive and evaluate biomarker combinations.
In: PLOS ONE 9(1), e84483 [PDF, 442kB]
In: PLOS ONE 9(1), e84483 [PDF, 442kB]
2013
Schmid, Matthias; Wickler, Florian; Maloney, Kelly O.; Mitchell, Richard; Fenske, Nora und Mayr, Andreas
(2013):
Boosted beta regression.
In: PLOS ONE 8(4), e61623 [PDF, 1MB]
In: PLOS ONE 8(4), e61623 [PDF, 1MB]
Schmid, Matthias; Wickler, Florian; Maloney, Kelly O.; Mitchell, Richard; Fenske, Nora und Mayr, Andreas
(2013):
Boosted Beta regression.
In: PLOS ONE 8(4), e61623 [PDF, 1MB]
In: PLOS ONE 8(4), e61623 [PDF, 1MB]
2012
Hofner, Benjamin; Mayr, Andreas; Robinzonov, Nikolay und Schmid, Matthias
(14. Februar 2012):
Model-based Boosting in R: A Hands-on Tutorial Using the R Package mboost.
Department of Statistics: Technical Reports, Nr. 120
[PDF, 784kB]
Mayr, Andreas; Fenske, Nora; Hofner, Benjamin; Kneib, Thomas und Schmid, Matthias
(2012):
Generalized additive models for location scale and shape for high-dimensional data - a flexible approach based on boosting.
In: Journal of the Royal Statistical Society, Series C (Applied Statistics), Bd. 61: S. 403-427
Mayr, Andreas; Hothorn, Torsten und Fenske, Nora
(2012):
Prediction intervals for future BMI values of individual children - A non-parametric approach by quantile boosting.
In: BMC Medical Research Methodology, Bd. 12: S. 6
Hofner, Benjamin; Mayr, Andreas; Robinzonov, Nikolay und Schmid, Matthias
(2012):
Model-based boosting in R: a hands-on tutorial using the R package mboost.
In: Computational Statistics: S. 1-33
Mayr, Andreas; Hothorn, Torsten und Fenske, Nora
(2012):
Prediction intervals for future BMI values of individual children - a non-parametric approach by quantile boosting.
In: BMC Medical Research Methodology
12:6
[PDF, 770kB]
2010
Mayr, Andreas; Fenske, Nora; Hofner, Benjamin; Kneib, Thomas und Schmid, Matthias
(13. Dezember 2010):
GAMLSS for high-dimensional data – a flexible approach based on boosting.
Department of Statistics: Technical Reports, Nr. 98
[PDF, 2MB]
Mayr, Andreas
(2010):
Prediction Inference with Ensemble Methods.
Diplomarbeit,
Ludwig-Maximilians-Universität München
[PDF, 3MB]
[PDF, 3MB]