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Bayesian astrophysics

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 pursu...

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Detalles Bibliográficos
Autores principales: Ramos, Andrés Asensio, Arregui, Íñigo
Lenguaje:eng
Publicado: Cambridge University Press 2018
Materias:
Acceso en línea:https://dx.doi.org/10.1017/9781316182406
http://cds.cern.ch/record/2706239
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author Ramos, Andrés Asensio
Arregui, Íñigo
author_facet Ramos, Andrés Asensio
Arregui, Íñigo
author_sort Ramos, Andrés Asensio
collection CERN
description 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.
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spelling cern-27062392021-04-21T18:11:48Zdoi:10.1017/9781316182406http://cds.cern.ch/record/2706239engRamos, Andrés AsensioArregui, ÍñigoBayesian astrophysicsAstrophysics and AstronomyBayesian 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.Cambridge University Pressoai:cds.cern.ch:27062392018
spellingShingle Astrophysics and Astronomy
Ramos, Andrés Asensio
Arregui, Íñigo
Bayesian astrophysics
title Bayesian astrophysics
title_full Bayesian astrophysics
title_fullStr Bayesian astrophysics
title_full_unstemmed Bayesian astrophysics
title_short Bayesian astrophysics
title_sort bayesian astrophysics
topic Astrophysics and Astronomy
url https://dx.doi.org/10.1017/9781316182406
http://cds.cern.ch/record/2706239
work_keys_str_mv AT ramosandresasensio bayesianastrophysics
AT arreguiinigo bayesianastrophysics