Julie Josse

Julie Josse
country
country

AgreenSkills session, year: 2nd session, 2012

Receiving laboratory: Department of Statistics, Stanford University, Palo Alto, California, USA

Country of origin : France

E-Mail: josse@agrocampus-ouest.fr

 

 

Mobility project

MISSING VALUES IMPUTATION FOR MIXED DATA BASED ON PRINCIPAL COMPONENT METHODS

When analyzing data, missing values are ubiquitous and can occur for plenty of reasons: machines that fail, individuals who forget to answer some questions in a questionnaire, etc. Missing values are problematic since most statistical methods cannot be applied directly on incomplete data. The aim of the project was the development of new statistical methods (especially dedicated to the exploration and visualization of data) to handle missing values in order to provide users facing this problem with new practical solutions. The fields of application include genetics and food science. 

Biography & research interests

Julie Josse is an associate professor of Statistics at Agrocampus Ouest, Rennes, France. Her research interest focuses mainly on handling missing values in (and using) exploratory principal components methods such as principal component analysis (PCA) or Multiple Factor Analysis for multi-tables data. She is also interested in suggesting regularized versions of these methods. She is involved in the development of R packages associated to these topics (FactoMineR and missMDA) and has published one book in collaboration “R for statistics”.

Selected publications
  1. Josse, J. & Timmerman, M.E. & Kiers, H.A.L. (2013). Missing values in multi-level simultaneous component analysis. (online version) Chemometrics and Intelligent Laboratory Systems.
  2. Husson, F. & Josse, J. (2013). Handling missing values in Multiple Factor Analysis.  Food Quality and Preferences. 30 (2), pp 77–85
  3. Josse, J & Husson, F. (2013). Handling missing values in exploratory multivariate data analysis methods. Journal de la SFdS. 153 (2), pp. 79-99. Paper written for the best Ph.D doctoral thesis prize deliverd by the French Statisical Society
  4. Josse, J., Chavent, M., Liquet, B. & Husson, F. (2012). Handling missing values with Regularized Iterative Multiple Correspondence Analysis. Journal of classification. 29 (1), pp.91-116.
  5. Josse, J. & Husson, F. (2011). Selecting the number of components in PCA using cross-validation approximations.Computational Statististics and Data Analysis. 56 (6), pp. 1869-1879.
  6. Josse, J., Husson, H. & Pagès, J. (2011). Multiple imputation in PCA.  Advances in data analysis and classification. 5 (3), pp. 231-246.
  7. Josse, J., Husson, H. & Pagès, J. (2009). Gestion des données manquantes en Analyse en Composantes Principales. Journal de la SFdS. 150 (2), pp. 28-51.
  8. Josse, J., Pagès, J. & Husson, F. (2008). Testing the significance of the RV coefficient. Computational Statististics and Data Analysis. 53, pp. 82-91.
  9. Lê S., Josse, J., Husson, F. (2008). FactoMineR: an R package for multivariate analysis. Journal of Statistical Software. 25 (1), pp. 1-18.

Submitted papers – technical reports

  1. Josse, J. & Holmes, S (2013). Measures of dependence between random vectors
  2. and tests of independence. A survey. On Arxiv: http://arxiv-web3.library.cornell.edu/abs/1307.7383
  3. Verbanck, M. & Josse, J. & Husson, F. (2013). Regularized PCA to denoise and visualise data. In revision pdf arXiv:1301.4649. R code. readme.
  4.  Audigier, V., Husson, F. & Josse, J. (2013). A principal components method to impute mixed data. In revision pdf arXiv:1301.4797.
  5. Josse, J.,  van Eeuwijk, F., Piepho, H-P, Denis, J.B. (2013). Another look at Bayesian analysis of AMMI models for genotype-environment data. Submitted.
  6. Josse, J. & Husson, F. (2013). Book chapter. Multiple correspondence analysis. To appear soon in The Visualization and Verbalization of Data.
  7. Josse, J., Fujii, H., Husson, F., & Ono, M. (2012). A semi-automatic computational method to identify FOXP3+T cell subpopulations in melanoma patients. JOURNAL OF INVESTIGATIVE DERMATOLOGY, 132, S5.
Awards & patents

Ph.D. dissertation award (Marie-Jeanne Laurent-Duhamel – French Statistical Society), 2012:

its aim is to reward the quality of a young, french-speaking statistician’s doctoral thesis. In

2012, it distinguishes a notable contribution to applied statistical research. http://www.sfds.asso.fr/

http://www.sfds.asso.fr/

In

2012, it distinguishes a notable contribution to applied statistical research.

http://www.sfds.asso.fr/

2012, it distinguishes a notable contribution to applied statistical research.

http://www.sfds.asso.fr/

Contact:

E-Mail: josse@agrocampus-ouest.fr

Website(s): http://math.agrocampus-ouest.fr/infoglueDeliverLive/membres/julie.josse/ | http://math.agrocampus-ouest.fr/infoglueDeliverLive/

CV: Download curriculum vitae