Bayesian astrophysics / edited by Andrés Asensio Ramos (Instituto de Astrofísica de Canarias, Tenerife), Iñigo Arregui (Instituto de Astrofísica de Canarias, Tenerife).
"Bayesian methods are increasingly being employed in many different areas of physical sciences research. In astrophysics, models are used to make predictions to compare to observations that are incomplete and uncertain, so the comparison must be pursued by following a probabilistic approach. Wi...
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| Online Access: |
Full Text (via Cambridge) |
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| Corporate Author: | |
| Other Authors: | , |
| Format: | Electronic Conference Proceeding eBook |
| Language: | English |
| Published: |
Cambridge, United Kingdom :
Cambridge University Press,
2018.
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| Series: | Canary Islands Winter School of Astrophysics (Series) ;
v. XXVI. |
| Subjects: |
| Summary: | "Bayesian methods are increasingly being employed in many different areas of physical sciences research. In astrophysics, models are used to make predictions to compare to observations that are incomplete and uncertain, so the comparison must be pursued by following a probabilistic approach. With contributions from leading experts, this volume covers the foundations of Bayesian inference, a description of the applicable computational methods, and recent results from their application to areas such as exoplanet detection and characterisation, image reconstruction, and cosmology. With content that appeals both to young researchers seeking to learn about Bayesian methods and to astronomers wishing to incorporate these approaches into their research, it provides the next generation of researchers with tools of modern data analysis that are becoming standard in astrophysical research"-- |
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| Item Description: | Lectures presented at the XXVI Canary Islands Winter School of Astrophysics, held in La Laguna, Tenerife, Spain, Nov. 3-14, 2014. |
| Physical Description: | 1 online resource |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 9781108619837 1108619835 9781316182406 1316182401 1107499585 9781107499584 |
| DOI: | 10.1017/9781316182406 |
| Source of Description, Etc. Note: | Source of description: Print version record. |