Vincent Audigier

Maître de conférences
Bureau : 35.3.21

2023

Articles de revue

  1. Mu~noz, J.; Efthimiou, O.; Audigier, V.; de Jong, V. and Debray, T. Multiple imputation of incomplete multilevel data using Heckman selection models. In Statistics in Medicine, 2023. doi  www 

Chapitres d'ouvrage

  1. Ameur, Y.; Bouzefrane, S. and Audigier, V. Application of Homomorphic Encryption in Machine Learning. In Emerging Trends in Cybersecurity Applications, pages 391-410, Springer International Publishing, 2023. doi  www 

Articles de conférence

  1. Audigier, V. and Niang, N. Multiple imputation for clustering on incomplete data. In ClaDAG 2023, Salerno (Italy), Italy, 2023. www 
  1. Audigier, V. and Sadou Zouleya, F. Clustering sur données incomplètes : méthodes directes ou imputation multiple ?. In Les 54èmes Journées de Statistique, Bruxelles, Belgium, 2023. www 

Non publié

  1. Mu~noz, J.; Egger, M.; Efthimiou, O.; Audigier, V.; de Jong, V. M. T. and Debray, Thomas. P. A. Multiple imputation of incomplete multilevel data using Heckman selection models. , 18 pages, 7 figures. www 
  1. Mouhou, E.; Audigier, V. and Noirel, J. A simple Bayesian model to estimate proportions and ratios from count data with a hierarchical error structure with an application to droplet digital PCR experiments. , working paper or preprint. www 

2022

Articles de revue

  1. Audigier, V. and Niang, N. Clustering with missing data: which equivalent for Rubin's rules?. In Advances in Data Analysis and Classification, 2022. doi  www 
  1. Bar-Hen, A. and Audigier, V. An ensemble learning method for variable selection: application to high dimensional data and missing values. In Journal of Statistical Computation and Simulation, 2022. doi  www 

Chapitres d'ouvrage

  1. Audigier, V. Gestion des données manquantes par imputation multiple. In Données manquantes, Editions TECHNIP, 2022. www 
  1. Audigier, V. Imputation multiple en grande dimension par analyse factorielle. In Données manquantes, Editions TECHNIP, 2022. www 

Articles de conférence

  1. Audigier, V.; Niang, N. and Resche-Rigon, M. Clustering with missing data: which imputation model for which cluster analysis method?. In 17th conference of the International Federation of Classification Societies, Porto, Portugal, 2022. www 
  1. Audigier, V.; Resche-Rigon, M. and Bonneville, E. F Gestion des données manquantes pour les analyses de survie. In EPICLIN 2022, 29èmes journées des statisticiens des CLCC, Paris, France, 2022. www 
  1. Ameur, Y.; Aziz, R.; Audigier, V. and Bouzefrane, S. Secure and non-interactive k-NN classifier using symmetric fully homomorphic encryption. In Privacy in statistical databases (PSD'2022), pages 142-154, Springer International Publishing, Paris, France, Lecture Notes in Computer Science 13463, 2022. doi  www 

2021

Articles de revue

  1. Moins-Teisserenc, H.; Cordeiro, D. J.; Audigier, V.; Ressaire, Q.; Benyamina, M.; Lambert, J.; Maki, G.; Homyrda, L.; Toubert, A. and Legrand, M. Severe Altered Immune Status After Burn Injury Is Associated With Bacterial Infection and Septic Shock. In Frontiers in Immunology, 12: 586195, 2021. doi  www 

Articles de conférence

  1. Audigier, V. and Niang, N. Cluster analysis after multiple imputation. In ASMDA 2021, Athènes, Greece, 2021. www 
  1. Hassini, H.; Niang, N. and Audigier, V. SOM-based clusterwise regression. In Data Science, Statistics and Visualisation, Rotterdam, Netherlands, 2021. www 
  1. Audigier, V.; Niang, N. and Resche-Rigon, M. Clustering sur données incomplètes~: quel modèle d'imputation choisir~?. In EPICLIN 2021 -- 15e Conférence francophone d'épidémiologie clinique -- 28e Journées des statisticiens des centres de lutte contre le cancer, pages S21-S22, Elsevier Masson, Marseille, France, 2021. doi  www 

Non publié

  1. Audigier, V.; Niang, N. and Resche-Rigon, M. Clustering with missing data: which imputation model for which cluster analysis method?. , working paper or preprint. www 

2020

Articles de revue

  1. Mirouse, A.; Parrot, A.; Audigier, V.; Demoule, A.; Mayaux, J.; Geri, G.; Mariotte, E.; Bréchot, N.; de Prost, N.; Vautier, M.; Neuville, M.; Bigé, N.; de Montmollin, E.; Cacoub, P.; Resche-Rigon, M.; Cadranel, J. and Saadoun, D. Severe diffuse alveolar hemorrhage related to autoimmune disease: a multicenter study. In Critical Care, 24 (1), 2020. doi  www 

Non publié

  1. Audigier, V. and Niang, N. Clustering with missing data: which equivalent for Rubin's rules?. , 39 pages. www 

2019

Articles de conférence

  1. Audigier, V.; Husson, F. c.; Josse, J. and Resche-Rigon, M. Imputation multiple pour données mixtes par analyse factorielle. In JdS2019 - 51es Journées de Statistique de la Société Franc caise de Statistique, Vandoeuvre-lès-Nancy, France, 2019. www 
  1. Audigier, V. and Resche Rigon, M. micemd: a smart multiple imputation R package for missing multilevel data. In UseR!2019, Toulouse, France, 2019. www 
  1. Faucheux, L.; Resche-Rigon, M.; Audigier, V.; Curis, E.; Soumelis, V. and Chevret, S. Clustering with missing data: Pooling multiple imputation results with consensus clustering. In 40th Annual Conference of the International Society for Clinical Biostatistics, Leuven (BE), Belgium, 2019. www 

2018

Articles de revue

  1. Audigier, V.; White, I.; Jolani, S.; Debray, T.; Quartagno, M.; Carpenter, J.; van Buuren, S. and Resche-Rigon, M. Multiple Imputation for Multilevel Data with Continuous and Binary Variables. In Statistical Science, 33 (2): 160-183, 2018. doi  www 

Articles de conférence

  1. Audigier, V.; White, I.; Jolani, S.; Debray, Thomas. P. A.; van Buuren, S. and Resche-Rigon, M. Multiple imputation for multilevel data with continuous and binary variables. In Journée de rencontres scientifiques autour de la statistique pour la biologie et la médecine, Poitiers (Université de Poitiers), France, 2018. www 
  1. Audigier, V.; White, I.; Jolani, S.; Debray, Thomas. P. A.; Quartagno, M.; van Buuren, S. and Resche-Rigon, M. Multiple imputation for multilevel data with continuous and binary variables. In Chimiométrie XIX, CNAM Paris, France, 2018. www 
  1. Bar-Hen, A. and Audigier, V. Une méthode dénsemble pour la sélection de variables : application `a la grande dimension et aux données manquantes. In 50emes journées de la statistique, Saclay, France, 2018. www 

2017

Articles de revue

  1. Audigier, V.; Husson, F. c. and Josse, J. MIMCA: Multiple imputation for categorical variables with multiple correspondence analysis. In Statistics and Computing, 27 (2): 501-518, 2017. doi  www 

2016

Articles de revue

  1. Audigier, V.; Husson, F. c. and Josse, J. Multiple imputation for continuous variables using a Bayesian principal component analysis. In Journal of Statistical Computation and Simulation, 86 (11): 2140-2156, 2016. doi  www 
  1. Audigier, V.; Husson, F. c. and Josse, J. A principal components method to impute missing values for mixed data. In Advances in Data Analysis and Classification, 10 (1): 5-26, 2016. doi  www 

2015

Thèses et habilitations

  1. Audigier, V. Imputation multiple par analyse factorielle : Une nouvelle méthodologie pour traiter les données manquantes. Ph.D. Thesis, Agrocampus Ouest, 2015.

2012

Articles de conférence

  1. Audigier, V.; Husson, F. c. and Josse, J. Imputation de données manquantes pour des données mixtes via les méthodes factorielles grâce `a missMDA. In 1ères Rencontres R, Bordeaux, France, 2012. www 
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