Research topics

Keywords: missing data, multiple imputation, factorial analysis, multilevel data, random forests, Bayesian
PhD thesis: Multiple imputation using principal component methods: a new methodology to deal with missing values
Manuscript (in french) - PhD defense (in english)

Papers

  1. Audigier, V., Husson, F. & Josse, J. (2016). A principal components method to impute mixed data. Advances in Data Analysis and Classification. pdf - bib - material - R package.
  2. Audigier, V., Husson, F. & Josse, J. (2016). Multiple imputation for continuous variables using a Bayesian principal component analysis. Journal of Statistical Computation and Simulation. pdf - bib - material - R package.
  3. Audigier, V., Husson, F. & Josse, J. (2017). MIMCA: Multiple imputation for categorical variables with multiple correspondence analysis. Statistics and Computing. pdf - bib - data - material - R package
  4. Audigier, V., White, I. ,  Jolani , S.  Debray, T.,  Quartagno, M., Carpenter, J., van Buuren, S. and Resche-Rigon, M. (2018)
    Multiple imputation for multilevel data with continuous and binary variables. Statistical Science. pdf - bib - material - R package
  5. Bar-Hen, A. & Audigier, V. An ensemble learning method for variable selection: application to high dimensional data and missing values. pdf

Conferences

  1. Audigier, V., Josse, J. & Husson, F. (2012): Missing values imputation for mixed data based on principal component methods.  COMPSTAT, Cyprus, August 27-31th. slides.
  2. Audigier, V., Josse, J. & Husson, F. (2012): Imputation de données manquantes pour des données mixtes via les méthodes factorielles grâce à missMDA. abstract - slides. Premières rencontres R, Bordeaux, July 2-3th.
  3. Audigier, V., Josse, J. & Husson, F. (2013): Imputation multiple a l'aide des methode d'analyse factorielle. 45eme Journees de Statistique, Toulouse, Mai 27-31th. abstract - slides
  4. Josse, J.,  Husson, F., Audigier, V. (2013). Imputation of mixed data: Random Forests versus PCA. ERCIM, London, December, 14-16th. slides
  5. Audigier, V., Josse, J. & Husson, F. (2014): Multiple imputation with Bayesian PCA. 46eme Journees de Statistique, Rennes, June 2-6th. abstract - slides.
  6. Audigier, V., Josse, J. & Husson, F. (2014): Multiple imputation with MCA. Journées de Statistique de Rennes, Rennes, October 23-24th. slides.
  7. Audigier, V., Josse, J. & Husson, F. (2015): Multiple imputation with MCA. 47eme Journées de Statistique, Lille, June 1-5th. slides.
  8. Audigier, V., Josse, J. & Husson, F. (2015): Multiple imputation for categorical data using MCA. missData2015, Rennes, June 17-19th. slides.
  9. Audigier, V., Josse, J. & Husson, F. (2015): Multiple imputation with MCA. CARMES, Naples, September 21-23th. slides.
  10. Audigier, V., Josse, J. & Husson, F. (2015): Multiple imputation with MCA. Rencontres doctorales Lebesgue, Nantes, October 28-30th. slides.
  11. Audigier, V., White, I. ,  Jolani ,S.  Debray, T.,  Quartagno, M. van Buuren S. & Resche-Rigon, M. (2016): Comparison of multiple imputation methods for systematically and sporadically missing multilevel data. Journées GDR / SFB, Lyon, June, 27-28th. slides
  12. Audigier, V., White, I. ,  Jolani ,S.  Debray, T.,  Quartagno, M. van Buuren S. & Resche-Rigon, M. (2016): Comparison of multiple imputation methods for systematically and sporadically missing multilevel data. ISCB, Birmingham, August, 21-25th. slides
  13. Audigier, V., White, I. ,  Jolani ,S.  Debray, T.,  Quartagno, M. van Buuren S. & Resche-Rigon, M. (2017): Multiple imputation for multilevel data with continuous and binary variables. SMB, Paris, September, 14-15th. poster
  14. Audigier, V., White, I. ,  Jolani ,S.  Debray, T.,  Quartagno, M. van Buuren S. & Resche-Rigon, M. (2018): Multiple imputation for multilevel data with continuous and binary variables. Chimiometrie 2018, Paris, January, 30-31st. slides
  15. Audigier, V., White, I. ,  Jolani ,S.  Debray, T.,  Quartagno, M. van Buuren S. & Resche-Rigon, M. (2018): Multiple imputation for multilevel data with continuous and binary variables. Journée de rencontres scientifiques autour de la statistique pour la biologie et la médecine, Poitiers, February, 1st. slides
  16. Bar-Hen, A. and Audigier, V. (2018): Une méthode d'ensemble pour la sélection de variables : application à la grande dimension et aux données manquantes. 50eme journée de la statistique. Saclay, May 28th - June 1st. slides

Seminars


  1. Josse, J., Husson F., Audigier, V. (2014). Multiple imputation with Bayesian PCA. Séminaire de l'institut de mathématiques de Bordeaux, March 6th. slides
  2. Audigier, V., Josse, J. & Husson, F. (2015): Multiple imputation using principal component methods. SBIM Seminar, Paris, July 15th. slides.
  3. Audigier, V., Josse, J. & Husson, F. (2016): Multiple imputation with principal component methods. Séminaire de l'ISPED, Bordeaux, March, 14th. slides.
  4. Audigier, V., Josse, J. & Husson, F. (2016): Multiple imputation with principal component methods. Midia meeting, London, March, 23th. slides.
  5. Audigier, V., Josse, J. & Husson, F. (2016): Multiple imputation with principal component methods. Séminaire de l'IRMA, Strasbourg, March, 29th. slides.
  6. Audigier, V., White, I. ,  Jolani ,S.  Debray, T.,  Quartagno, M. van Buuren S. & Resche-Rigon, M. (2016): Comparison of multiple imputation methods for systematically and sporadically missing multilevel data. Midia meeting, London, September, 28th. slides.
  7. Audigier, V., White, I. ,  Jolani ,S.  Debray, T.,  Quartagno, M. van Buuren S. & Resche-Rigon, M. (2016): Comparison of multiple imputation methods for systematically and sporadically missing multilevel data. Séminaire de l'équipe INRIA MODAL, Lille, November, 22th. slides
  8. Audigier, V. (2017): Some contributions for handling missing values by multiple imputation. Séminaire de statistique appliquée du CNAM. Paris, September, 29th. slides
  9. Audigier, V., Josse, J. & Husson, F. (2017): Multiple imputation with principal component methods. Data Science Seminar de Telecom Paristech, Paris, November, 16th. slides.
  10. Audigier, V., White, I. ,  Jolani ,S.  Debray, T.,  Quartagno, M. van Buuren S. & Resche-Rigon, M. (2017): Multiple imputation for multilevel data with continuous and binary variables. Séminaire de Statistique et Probabilités Appliquées du LJK, Grenoble, December, 14th. slides
  11. Bar-Hen, A. and Audigier, V. (2018): An ensemble learning method for variable selection: application to high dimensional data and missing values. Midia meeting, London, November, 28th