9 citations · 22 across the 10 of their papers we have counts for
4 papers · 1 filter
Addressing cluster-constant covariates in mixed effects models via likelihood-based boosting techniques
Colin Griesbach, Andreas Groll, Elisabeth Waldmann
Boosting techniques from the field of statistical learning have grown to be a popular tool for estimating and selecting predictor effects in various regression models and can rough…
Generalised Joint Regression for Count Data with a Focus on Modelling Football Matches
Hendrik van der Wurp, Andreas Groll, Thomas Kneib +2
We propose a versatile joint regression framework for count responses. The method is implemented in the R add-on package GJRM and allows for modelling linear and non-linear depende…
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…
Prediction of the 2019 IHF World Men's Handball Championship - An underdispersed sparse count data regression model
Andreas Groll, Jonas Heiner, Gunther Schauberger +1
In this work, we compare several different modeling approaches for count data applied to the scores of handball matches with regard to their predictive performances based on all ma…