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Statistics For Astrophysics Bayesian Methodology 1st Edition Jeanbaptiste Marquette Didier Fraixburnet Stphane Girard Julyan Arbel

  • SKU: BELL-51659678
Statistics For Astrophysics Bayesian Methodology 1st Edition Jeanbaptiste Marquette Didier Fraixburnet Stphane Girard Julyan Arbel
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Statistics For Astrophysics Bayesian Methodology 1st Edition Jeanbaptiste Marquette Didier Fraixburnet Stphane Girard Julyan Arbel instant download after payment.

Publisher: EDP Sciences
File Extension: PDF
File size: 14.4 MB
Pages: 140
Author: Jean-Baptiste Marquette; Didier Fraix‐Burnet; Stéphane Girard; Julyan Arbel
ISBN: 9782759822751, 2759822753
Language: English
Year: 2018
Edition: 1

Product desciption

Statistics For Astrophysics Bayesian Methodology 1st Edition Jeanbaptiste Marquette Didier Fraixburnet Stphane Girard Julyan Arbel by Jean-baptiste Marquette; Didier Fraix‐burnet; Stéphane Girard; Julyan Arbel 9782759822751, 2759822753 instant download after payment.

This book includes the lectures given during the third session of the School of Statistics for Astrophysics that took place at Autrans, near Grenoble, in France, in October 2017. The subject is 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 luctuations. The cosmological community has thus been very active in this field for many years. But the Bayesian methodology, complementary to the more classical frequentist one, has many applications in physics in general due to its ability to incorporate a priori knowledge into inference, such as uncertainty brought by the observational processes. The Bayesian approach becomes more and more widespread in the astrophysical literature. This book contains statistics courses on basic to advanced methods with practical exercises using the R environment, by leading experts in their field. This covers the foundations of Bayesian inference, Markov chain Monte Carlo technique, model building, Approximate Bayesian Computation (ABC) and Bayesian nonparametric inference and clustering.

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