The primary goal of the School of Statistics for Astrophysics 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 works in common, to give firm grounds to the theoretical lessons, and to initiate works on problems brought by the participants. There have been two previous sessions of this school, one on regression and one on clustering and classification.

The School of Statistics for Astrophysics 2017 will be devoted to the  Bayesian Methodology. The interest of this statistical approach in astrophysics probably comes from its necessity and its success in determining the cosmological parameters from observations, especially from the cosmic background fluctuations.  The cosmological community has thus been very active in this field (see for instance the Cosmostatistics Initiative COIN). 

But the Bayesian methodology, complementary to the more classical frequentist one, has many applications in physics in general due to its faculty to incorporate a priori knowledge into the inference computation, such as the uncertainties brought by the observational processes.

As for sophisiticated statistical techniques, astronomers are not familiar with Bayesian methodology in general, while it is becoming more and more widespread and useful in the literature. This school will form the participants to both a strong theoretical background and a solid practice of Bayesian inference.


Didier Fraix-Burnet (IPAG)

Stéphane Girard (Inria)

Julyan Arbel (Inria)

Jean-Baptiste Marquette (IAP)

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