Methods and Applications of Regression in Astrophysics
21-25 Oct 2013 Annecy (France)


During the last decades, astronomy has come to a new age with the avalanche of available data. Important needs for complex statistical tools and skills have emerged. In turn this new paradigm has fostered a strong interest for the research in statistics itself.


The primary goal of the École d'Astrostatistique is to train astronomers to the use of modern statistical techniques. It also aims at bridging the gap between the two communities by emphasizing on the practice during concrete works in common, to give firm grounds to the theoretical lessons, and to initiate works on problems brought by the participants. Finally, some talks will show some current research from both communities, leading to a better reciprocal knowledge of the two communities as well as an initiatiion of discussions between two cultures with different jargons.


We have chosen to concentrate this École d'Astrostatistique 2013 on the regression, which is the art to predict, or explain a variable called dependent, to be predicted or explained, from variables called independent, predictive or explicatives. This theme is central in astrophysics where the data analysis, the understanding of the different parameters and observables, and the fitting to models, are ubiquitous.



This school is a  École Thématique du CNRS 2013.  from the Formation Permanente that fully supports the participation of CNRS personnel.

This school is of course opened to any astronomer.

No specific knowledge of statistics is required, and the mathematical background of all astronomers is sufficient to attend the school.


Organizing committee

Scientific Committee


Organisation Committee

D. Fraix-Burnet (IPAG)       D. Fraix-Burnet (IPAG)
 D. Valls-Gabaud (Obs Paris)        D. Valls-Gabaud (Obs Paris)
 J.-L. Starck (CEA)        T. Dudok de Wit (LPC2E)
 E. Slezak (OCA)        P. Gratier (IRAM)
 T. Dudok de Wit (LPC2E)        S. Girard (Inria)
 S. Girard (Inria)        R. Stoica(Univ. Lille)
 J. Jacques (Univ. Lille 1/Inria)        J. Jacques (Univ. Lille 1/Inria)
         M. Clausel (IMAG)
         G. Grégoire (IMAG)



      CNRS                             LabexOSUG  Investissement d'Avenir                


Supported by INSU

INRIA                ljkLagrange






Online user: 1