Gradient boosting for extreme quantile regression J Velthoen, C Dombry, JJ Cai, S Engelke Extremes 26 (4), 639-667, 2023 | 46 | 2023 |
Improving precipitation forecasts using extreme quantile regression J Velthoen, JJ Cai, G Jongbloed, M Schmeits Extremes 22, 599-622, 2019 | 24 | 2019 |
Forward variable selection for random forest models J Velthoen, JJ Cai, G Jongbloed Journal of Applied Statistics 50 (13), 2836-2856, 2023 | 2 | 2023 |
Non-parametric extreme quantile estimation for the common shaped tail model JJ Velthoen Delft: Mathematics and Computer Science, TU Delft, 2016 | 2 | 2016 |
Estimating the extreme value index for imprecise data JJ Velthoen | 2 | 2014 |
Interpretable random forest models through forward variable selection J Velthoen, JJ Cai, G Jongbloed arXiv preprint arXiv:2005.05113, 2020 | 1 | 2020 |
Statistical post processing of extreme weather forecasts JJ Velthoen | | 2022 |
Non-parametric extreme quantile estimation for the common shaped tail model: Forecasting extreme precipitation by post-processing precipitation from a numerical weather … JJ Velthoen | | 2016 |
Schatten van de extreme value index voor afgeronde data (Engelse titel: Estimation of the extreme value index for imprecise data) JJ Velthoen | | 2014 |