| Transforming variables to central normality J Raymaekers, PJ Rousseeuw Machine Learning 113 (8), 4953-4975, 2024 | 78 | 2024 |
| A measure of directional outlyingness with applications to image data and video PJ Rousseeuw, J Raymaekers, M Hubert Journal of Computational and Graphical Statistics 27 (2), 345-359, 2018 | 67 | 2018 |
| Fast robust correlation for high-dimensional data J Raymaekers, PJ Rousseeuw Technometrics 63 (2), 184-198, 2021 | 55 | 2021 |
| cellWise: Analyzing data with cellwise outliers J Raymaekers, P Rousseeuw, W Van den Bossche, M Hubert CRAN, R package version 2 (0), 467, 2019 | 32 | 2019 |
| mrfDepth: Depth measures in multivariate, regression and functional settings P Segaert, M Hubert, P Rousseeuw https://cran. r-project. org/package= mrfDepth, 2017 | 28 | 2017 |
| The cellwise minimum covariance determinant estimator J Raymaekers, PJ Rousseeuw Journal of the American Statistical Association 119 (548), 2610-2621, 2024 | 26 | 2024 |
| A generalized spatial sign covariance matrix J Raymaekers, P Rousseeuw Journal of Multivariate Analysis 171, 94-111, 2019 | 23 | 2019 |
| Handling cellwise outliers by sparse regression and robust covariance J Raymaekers, PJ Rousseeuw Journal of Data Science, Statistics, and Visualisation 1 (3), 2021 | 20 | 2021 |
| Challenges of cellwise outliers J Raymaekers, PJ Rousseeuw Econometrics and Statistics, 2024 | 19 | 2024 |
| Mcr: Method comparison regression S Potapov, IF Mode, A Schuetzenmeister, E Manuilova, F Dufey, ... R package version 1 (2), 2023 | 17 | 2023 |
| Real-time discriminant analysis in the presence of label and measurement noise I Vranckx, J Raymaekers, B De Ketelaere, PJ Rousseeuw, M Hubert Chemometrics and Intelligent Laboratory Systems 208, 104197, 2021 | 16 | 2021 |
| Real-time outlier detection for large datasets by RT-DetMCD B De Ketelaere, M Hubert, J Raymaekers, PJ Rousseeuw, I Vranckx Chemometrics and Intelligent Laboratory Systems 199, 103957, 2020 | 16 | 2020 |
| Class maps for visualizing classification results J Raymaekers, PJ Rousseeuw, M Hubert Technometrics 64 (2), 151-165, 2022 | 12 | 2022 |
| Weight-of-evidence through shrinkage and spline binning for interpretable nonlinear classification J Raymaekers, W Verbeke, T Verdonck Applied Soft Computing 115, 108160, 2022 | 11 | 2022 |
| Pooled variable scaling for cluster analysis J Raymaekers, RH Zamar Bioinformatics 36 (12), 3849-3855, 2020 | 10 | 2020 |
| Silhouettes and quasi residual plots for neural nets and tree-based classifiers J Raymaekers, PJ Rousseeuw Journal of Computational and Graphical Statistics 31 (4), 1332-1343, 2022 | 9 | 2022 |
| Finding outliers in surface data and video M Hubert, J Raymaekers, PJ Rousseeuw, P Segaert arXiv preprint arXiv:1601.08133, 2016 | 9 | 2016 |
| Cellwise: Analyzing data with cellwise outliers. R package version 2.2. 5 J Raymaekers, P Rousseeuw URL https://CRAN. R-project. org/package= cellWise, 2023 | 7 | 2023 |
| Fast linear model trees by PILOT J Raymaekers, PJ Rousseeuw, T Verdonck, R Yao arXiv preprint arXiv:2302.03931, 2023 | 6 | 2023 |
| cellWise: Analyzing data with cellwise outliers, 2016 J Raymaekers, P Rousseeuw, W Van den Bossche URL https://CRAN. R-project. org/package= cellWise. R package version 2 (10), 0 | 6 | |
Peter RousseeuwKU Leuven, BelgiumVerified email at rousseeuw.net