| FactoMineR: an R package for multivariate analysis S Lê, J Josse, F Husson Journal of statistical software 25, 1-18, 2008 | 10501 | 2008 |
| missMDA: a package for handling missing values in multivariate data analysis J Josse, F Husson Journal of statistical software 70, 1-31, 2016 | 1131 | 2016 |
| FactoMineR: multivariate exploratory data analysis and data mining with R F Husson, J Josse, S Le, J Mazet R package version 1 (1.29), 2013 | 999* | 2013 |
| Principal component methods-hierarchical clustering-partitional clustering: why would we need to choose for visualizing data F Husson, J Josse, J Pages Applied mathematics department 17, 2010 | 678 | 2010 |
| Package ‘factominer’ F Husson, J Josse, S Le, J Mazet, MF Husson An R package 96 (96), 698, 2016 | 533 | 2016 |
| Handling missing values in exploratory multivariate data analysis methods J Josse, F Husson Journal de la société française de statistique 153 (2), 79-99, 2012 | 337 | 2012 |
| Testing the significance of the RV coefficient J Josse, J Pagès, F Husson Computational Statistics & Data Analysis 53 (1), 82-91, 2008 | 303 | 2008 |
| Selecting the number of components in principal component analysis using cross-validation approximations J Josse, F Husson Computational Statistics & Data Analysis 56 (6), 1869-1879, 2012 | 272 | 2012 |
| Principal component analysis with missing values: a comparative survey of methods S Dray, J Josse Plant Ecology 216, 657-667, 2015 | 242 | 2015 |
| FactoMineR: an R package for multivariate analysis F Husson, J Josse, S Lê, J Mazet Journal of statistical software 25 (1), 1-18, 2008 | 198 | 2008 |
| A principal component method to impute missing values for mixed data V Audigier, F Husson, J Josse Advances in Data Analysis and Classification 10, 5-26, 2016 | 175 | 2016 |
| Multiple imputation in principal component analysis J Josse, J Pagès, F Husson Advances in data analysis and classification 5, 231-246, 2011 | 165 | 2011 |
| Missing data imputation using optimal transport B Muzellec, J Josse, C Boyer, M Cuturi International Conference on Machine Learning, 7130-7140, 2020 | 149 | 2020 |
| Handling missing values with regularized iterative multiple correspondence analysis J Josse, M Chavent, B Liquet, F Husson Journal of classification 29 (1), 91-116, 2012 | 145 | 2012 |
| Multiple correspondence analysis F Husson, J Josse Visualization and verbalization of data 22, 2014 | 143 | 2014 |
| Causal inference methods for combining randomized trials and observational studies: a review B Colnet, I Mayer, G Chen, A Dieng, R Li, G Varoquaux, JP Vert, J Josse, ... Statistical science 39 (1), 165-191, 2024 | 134 | 2024 |
| Adaptive conformal predictions for time series M Zaffran, O Féron, Y Goude, J Josse, A Dieuleveut International Conference on Machine Learning, 25834-25866, 2022 | 134 | 2022 |
| On the consistency of supervised learning with missing values J Josse, JM Chen, N Prost, G Varoquaux, E Scornet Statistical Papers 65 (9), 5447-5479, 2024 | 131 | 2024 |
| Statistiques avec R PA Cornillon, F Husson, N Jégou, E Matzner-Lober, J Josse, A Guyader, ... Lectures, Les livres, 2010 | 130 | 2010 |
| Measuring multivariate association and beyond J Josse, S Holmes Statistics surveys 10, 132, 2016 | 112 | 2016 |
François HussonProfessor in StatisticsVerified email at agrocampus-ouest.fr