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English
Cambridge University Press
26 April 2018
Bayesian methods are being increasingly employed in many different areas of research in the physical sciences. In astrophysics, models are used to make predictions to be compared to observations. These observations offer information that is incomplete and uncertain, so the comparison has to be pursued by following a probabilistic approach. With contributions from leading experts, this volume covers the foundations of Bayesian inference, a description of computational methods, and recent results from their application to areas such as exoplanet detection and characterisation, image reconstruction, and cosmology. It appeals to both young researchers seeking to learn about Bayesian methods as well as to astronomers wishing to incorporate these approaches in their research areas. It provides the next generation of researchers with the tools of modern data analysis that are already becoming standard in current astrophysical research.

Edited by:   , ,
Imprint:   Cambridge University Press
Country of Publication:   United Kingdom
Volume:   26
Dimensions:   Height: 254mm,  Width: 178mm,  Spine: 14mm
Weight:   570g
ISBN:   9781107102132
ISBN 10:   1107102138
Series:   Canary Islands Winter School of Astrophysics
Pages:   204
Publication Date:  
Audience:   Professional and scholarly ,  Undergraduate
Format:   Hardback
Publisher's Status:   Active

Andrés Asensio Ramos is an astrophysicist working as a researcher at the Instituto de Astrofísica de Canarias, Tenerife, Spain. where he also completed his Ph.D. His current research focuses on the interpretation of spectropolarimetric signals in the Sun and other stars to infer properties about the magnetic field. His interests in astrophysics are spectropolarimetry, solar and stellar physics and Bayesian inference. Íñigo Arregui is an astrophysicist working at the Instituto de Astrofísica de Canarias. He completed a Ph.D. in Physics at Universitat de les Illes Balears with a thesis on MHD waves in the solar atmosphere. His research focuses on the interpretation and modeling of wave activity in the solar atmosphere, designing tools for remote sensing of solar atmospheric plasmas, and the study of wave based plasma heating mechanisms.

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