Scientific publications of the members of the Research Center for Statistics are essentially in fundamental statistics (mathematical statistics), with focus in applied research fields such as financial econometrics, economics, health sciences, engineering, environmental sciences, psychology, social sciences, etc. More specifically, the researchers affiliated to the Center provide expertise on robust inference, small sample inference, indirect inference, semi- and non parametric statistics, model selection in high dimension, time series analysis, mixed and generalized linear latent variable models, longitudinal data analysis,
The members of the Research Center for Statistics are/have been members of editorial boards of statistical journals, such as the Journal of the American Statistical association, TEST, Sankhya B, Computational Statistics & Data Analysis, and other disciplinary journals such as the Journal of Income Inequality.
The members of the Center also organize or participate to the organization of scientific international conferences. The most recent include:
- 21st International Conference on Computational Statistics (COMPSTAT 2014), Geneva, August 2014. Organizer and Chairman: Prof. (emeritus) Manfred Gilli, Scientific and Organizing committees: Prof. Gérard Antille, Manfred Gilli, Stefan Sperlich, Elvezio Ronchetti
- International Conference on Robust Statistics (ICORS 2016), Geneva, June 2016. 200 participants. Organizer and Chairman: Prof. Maria-Pia Victoria-Feser, Scientific and Organizing committees: Prof. Eva Cantoni, Elvezio Ronchetti, Davide La Vecchia, Dr. Marc-Olivier Boldi.
- Workshop in honor of Prof. Elvezio Ronchetti's 60th birthday, Geneva, Saturday July 2nd, 2016. 60 participants. Organizers: Prof. Eva Cantoni, Prof. Davide La Vecchia, Prof. Fabio Trojani
- 31th annual congress of the European Economic Association & 69th European meeting of the Econometric Society (EEA-ESEM 2016), Geneva, August 2016. 1’500 participants.
The members of the Research Center for Statistics have been active in seeking outside funding for research projects. Many of our Ph. D. students are financed through these projects. The main source of financial support is the Swiss National Science Foundation, but other sources have also been used.
Hallin, M., & La Vecchia, D. (2018)
A Simple R-Estimation Method for Semiparametric Duration Models.
The Journal of Econometrics, forthcoming.
Avella-Medina, M., & Ronchetti, E. (2017).
Robust and Consistent Variable Selection in High-Dimensional Generalized Linear Models.
Biometrika, 105(1), 31–44. DOI: 10.1093/biomet/asx070
Cantoni, E., Mills Flemming, J., & Welsh, A. H. (2017).
A random-effects hurdle model for predicting bycatch of endangered marine species.
Annals of Applied Statistics, 11(4), 2178-2199. DOI: 10.1214/17-AOAS1074
Guerrier, S., Dupuis-Lozeron, E., Ma, Y. & Victoria-Feser, M.-P.
Simulation based Bias Correction Methods for Complex Models.
Journal of the American Statistical Association Theory and Methods Section, DOI: 10.1080/01621459.2017.1380031
Hallin, M., & La Vecchia, D. (2017).
R-estimation in semiparametric dynamic location-scale models.
Journal of Econometrics, 196(2), 233-247. DOI: 10.1016/j.jeconom.2016.08.002
Please consult our webpage on Knowledge and Publications
Recent Ph.D. Theses
Contributions to the robust analysis of structural models (Ranjbar, S. 2018)Validity and accuracy of posterior distributions in Bayesian statistics (Turbatu, L. 2018)
Contributions to Inference for Diffusion Processes and Robust Statistics (Deleamont, P. Y. 2017)
On the Inference for Random Effects in Generalized Linear Mixed Models (Flores Agreda, D. A. 2017)
Measures of Model Adequacy and Model Selection in Mixed-Effects Models (Jacot, N. 2017)
Robust Inference for Random Fields and Latent Models (Molinari, R. C. 2017)
Confidence Sets for Model Eslection (Hannay, N. 2016)
Robust Penalized M-Estimators for Generalized Linear and Additive Models (Avella Medina, N. A. 2016)
Time-Frequency Granger Causality with Application to Nonstationary Brain Signals (Cekic, S. 2015)
Simulation Based Bias Correction Methods for Complex Problems (Dupuis Lozeron, E. 2015)
Tree-Based Mathods for Moderated Regression With Application to Longitudinal Data (Buergin, R. A. 2015)
Contributions to Overdispersed Count Data Modeling: Robustness, Small Samples and Other Extensions (Aeberhard, W. 2015)