Statistics for Astrophysics

Bayesian Methodology

by Didier Fraix‐Burnet (technical editor), Jean-Baptiste Marquette, Stéphane Girard (technical editor), Julyan Arbel (technical editor)
december 2018
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140 pages Download after purchase
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Presentation

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.

Characteristics

Language(s): English

Publisher: EDP Sciences

Edition: 1st edition

Collection: EDP Sciences Proceedings

Published: 1 december 2018

EAN13 (hardcopy): 9782759822744

EAN13 eBook [PDF]: 9782759822751

Interior: Colour

Pages count eBook [PDF]: 140

Size: 15 Mo (PDF)