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Welcome

Institute of Statistics

 

The Institute of Statistics of the University of Neuchâtel provides bachelor and graduate courses included in the university program in management, social sciences, economy, labour psychology, informatics and mathematics. The Institute of Statistics additionally guarantees a master program in statistics. The research interests of the institute mainly concern sampling, estimation in finite populations, non-parametric and semi-parametric methods, multivariate statistics, robust methods, PLS regression. The Institute of Statistics develops a constant and productive collaboration with the Swiss Federal Statistical Office. Public as well as private enterprises entrust our Institute with several tasks

We have moved

New address : Av. de Bellevaux 51 (G building/Unimail), upper ground floor west, 2000 Neuchâtel

 

Recent publications

  • Tafin Djoko, D., & Tillé, Y. (2015). Selection of Balanced Portfolios to Track the Main Properties of a Large Market. Quantitative Finance, 15(2), 359-370.
  • Graf, M., & Nedyalkova, D. (2014). Modeling of income and indicators of poverty and social exclusion using the Generalized Beta Distribution of the Second Kind. Review of Income and Wealth, 60(4), 821-842.  lien internet
  •  Graf, E., & Tillé, Y. (2014). Variance Estimation Using Linearization for Poverty and Social Exclusion Indicators. Survey Methodology, 40(1), 61-79.  lien internet 
  • Grafström, A., & Matei, A. (2014). Coordination of Conditional Poisson Samples. accepted in Journal of Official Statistics, 1-2.
  •  Graf, E., & Qualité, L. (2014). Sondage dans des registres de population et de ménages en Suisse : coordination d’échantillons, pondération et imputation. Journal de la Société Française de Statistique, 155(4), 95-133.  lien internet
  • Graf, E., & Tillé, Y. (2014). Estimation de variance par linéarisation pour des indices de pauvreté et d’exclusion sociale. Techniques d'enquête, 40(1), 69-88.  lien internet 
  • Hasler, C., & Tillé, Y. (2014). Fast balanced sampling for highly stratified population. Computational Statistics & Data Analysis, 74, 81-94. lien internet