| From depth to local depth: a focus on centrality D Paindaveine, G Van Bever Journal of the American Statistical Association 108 (503), 1105-1119, 2013 | 96 | 2013 |
| Nonparametrically consistent depth-based classifiers D Paindaveine, G Van Bever Bernoulli, 62-82, 2015 | 46 | 2015 |
| Halfspace depths for scatter, concentration and shape matrices D Paindaveine, G Van Bever The Annals of Statistics 46 (6B), 3276-3307, 2018 | 39 | 2018 |
| Inference on the shape of elliptical distributions based on the MCD D Paindaveine, G Van Bever Journal of Multivariate Analysis 129, 125-144, 2014 | 12 | 2014 |
| Flexible integrated functional depths S Nagy, S Helander, G Van Bever, L Viitasaari, P Ilmonen | 6 | 2021 |
| The influence function of graphical lasso estimators G Louvet, J Raymaekers, G Van Bever, I Wilms Econometrics and Statistics, 2023 | 5 | 2023 |
| Tyler shape depth D Paindaveine, G Van Bever Biometrika 106 (4), 913-927, 2019 | 5 | 2019 |
| Geometry of goodness-of-fit testing in high dimensional low sample size modelling P Marriott, R Sabolova, G Van Bever, F Critchley International Conference on Geometric Science of Information, 569-576, 2015 | 5 | 2015 |
| Contributions to nonparametric and semiparametric inference based on statistical depth G Van Bever | 5 | 2013 |
| Pareto depth for functional data S Helander, G Van Bever, S Rantala, P Ilmonen Statistics 54 (1), 182-204, 2020 | 4 | 2020 |
| Simplicial bivariate tests for randomness G Van Bever Statistics & Probability Letters 112, 20-25, 2016 | 2 | 2016 |
| Additive regression with general imperfect variables JM Jeon, G Van Bever arXiv preprint arXiv:2212.05745, 2022 | 1 | 2022 |
| Integrated shape-sensitive functional metrics S Helander, P Laketa, P Ilmonen, S Nagy, G Van Bever, L Viitasaari Journal of Multivariate Analysis 189, 104880, 2022 | 1 | 2022 |
| On the maximal halfspace depth of permutation-invariant distributions on the simplex D Paindaveine, G Van Bever Statistics & Probability Letters 129, 335-339, 2017 | 1 | 2017 |
| Supplement to “Halfspace depths for scatter, concentration and shape matrices” D Paindaveine, G Van Bever Manuscript under consideration, 2017 | 1 | 2017 |
| The information geometry of sparse goodness-of-fit testing P Marriott, R Sabolová, G Van Bever, F Critchley Entropy 18 (12), 421, 2016 | 1 | 2016 |
| Bivariate simplicial tests for randomness G Van Bever Statistics and Probability Letters 112, 20-25, 2016 | 1 | 2016 |
| Discussion of “Multivariate Functional Outlier Detection”, by Mia Hubert, Peter Rousseeuw and Pieter Segaert D Paindaveine, G Van Bever Statistical methods & applications 24 (2), 223-231, 2015 | 1 | 2015 |
| On optimal prediction of missing functional data with memory P Ilmonen, N Shafik, T Sottinen, G Van Bever, L Viitasaari arXiv preprint arXiv:2208.09925, 2022 | | 2022 |
| Autoregression Depth D Paindaveine, G Van Bever Annales de l'ISUP 63 (2-3), 57-70, 2019 | | 2019 |