Bayesian models for astrophysical data: using R, JAGS, Python, and Stan
This comprehensive guide to Bayesian methods in astronomy enables hands-on work by supplying complete R, JAGS, Python, and Stan code, to use directly or to adapt. It begins by examining the normal model from both frequentist and Bayesian perspectives and then progresses to a full range of Bayesian g...
Gespeichert in:
| Hauptverfasser: | , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Cambridge
Cambridge University Press
2017
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| Schlagworte: | |
| Online-Zugang: | BSB01 FHN01 UER01 Volltext |
| Zusammenfassung: | This comprehensive guide to Bayesian methods in astronomy enables hands-on work by supplying complete R, JAGS, Python, and Stan code, to use directly or to adapt. It begins by examining the normal model from both frequentist and Bayesian perspectives and then progresses to a full range of Bayesian generalized linear and mixed or hierarchical models, as well as additional types of models such as ABC and INLA. The book provides code that is largely unavailable elsewhere and includes details on interpreting and evaluating Bayesian models. Initial discussions offer models in synthetic form so that readers can easily adapt them to their own data; later the models are applied to real astronomical data. The consistent focus is on hands-on modeling, analysis of data, and interpretations that address scientific questions. A must-have for astronomers, its concrete approach will also be attractive to researchers in the sciences more generally |
| Beschreibung: | Title from publisher's bibliographic system (viewed on 25 May 2017) |
| Beschreibung: | 1 online resource (xvii, 393 pages) |
| ISBN: | 9781316459515 |
| DOI: | 10.1017/CBO9781316459515 |
Internformat
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Datensatz im Suchindex
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| author | Hilbe, Joseph M. 1944-2017 Souza, Rafael S. de Ishida, Emille E. O. |
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| dewey-ones | 520 - Astronomy and allied sciences |
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| dewey-tens | 520 - Astronomy and allied sciences |
| discipline | Physik Informatik Mathematik |
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| id | DE-604.BV044447846 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T07:53:13Z |
| institution | BVB |
| isbn | 9781316459515 |
| language | English |
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| spelling | Hilbe, Joseph M. 1944-2017 Verfasser (DE-588)128751851 aut Bayesian models for astrophysical data using R, JAGS, Python, and Stan Joseph M. Hilbe, Rafael S. de Souza, Emille E.O. Ishida Cambridge Cambridge University Press 2017 1 online resource (xvii, 393 pages) txt rdacontent c rdamedia cr rdacarrier Title from publisher's bibliographic system (viewed on 25 May 2017) This comprehensive guide to Bayesian methods in astronomy enables hands-on work by supplying complete R, JAGS, Python, and Stan code, to use directly or to adapt. It begins by examining the normal model from both frequentist and Bayesian perspectives and then progresses to a full range of Bayesian generalized linear and mixed or hierarchical models, as well as additional types of models such as ABC and INLA. The book provides code that is largely unavailable elsewhere and includes details on interpreting and evaluating Bayesian models. Initial discussions offer models in synthetic form so that readers can easily adapt them to their own data; later the models are applied to real astronomical data. The consistent focus is on hands-on modeling, analysis of data, and interpretations that address scientific questions. A must-have for astronomers, its concrete approach will also be attractive to researchers in the sciences more generally Datenverarbeitung Statistical astronomy Statistical astronomy / Data processing Astronomy / Data processing Datenanalyse (DE-588)4123037-1 gnd rswk-swf Bayes-Verfahren (DE-588)4204326-8 gnd rswk-swf Astronomie (DE-588)4003311-9 gnd rswk-swf Astronomie (DE-588)4003311-9 s Datenanalyse (DE-588)4123037-1 s Bayes-Verfahren (DE-588)4204326-8 s DE-604 Souza, Rafael S. de Verfasser (DE-588)1134896271 aut Ishida, Emille E. O. Verfasser (DE-588)1134897197 aut Erscheint auch als Druck-Ausgabe, hardback 978-1-107-13308-2 https://doi.org/10.1017/CBO9781316459515 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Hilbe, Joseph M. 1944-2017 Souza, Rafael S. de Ishida, Emille E. O. Bayesian models for astrophysical data using R, JAGS, Python, and Stan Datenverarbeitung Statistical astronomy Statistical astronomy / Data processing Astronomy / Data processing Datenanalyse (DE-588)4123037-1 gnd Bayes-Verfahren (DE-588)4204326-8 gnd Astronomie (DE-588)4003311-9 gnd |
| subject_GND | (DE-588)4123037-1 (DE-588)4204326-8 (DE-588)4003311-9 |
| title | Bayesian models for astrophysical data using R, JAGS, Python, and Stan |
| title_auth | Bayesian models for astrophysical data using R, JAGS, Python, and Stan |
| title_exact_search | Bayesian models for astrophysical data using R, JAGS, Python, and Stan |
| title_full | Bayesian models for astrophysical data using R, JAGS, Python, and Stan Joseph M. Hilbe, Rafael S. de Souza, Emille E.O. Ishida |
| title_fullStr | Bayesian models for astrophysical data using R, JAGS, Python, and Stan Joseph M. Hilbe, Rafael S. de Souza, Emille E.O. Ishida |
| title_full_unstemmed | Bayesian models for astrophysical data using R, JAGS, Python, and Stan Joseph M. Hilbe, Rafael S. de Souza, Emille E.O. Ishida |
| title_short | Bayesian models for astrophysical data |
| title_sort | bayesian models for astrophysical data using r jags python and stan |
| title_sub | using R, JAGS, Python, and Stan |
| topic | Datenverarbeitung Statistical astronomy Statistical astronomy / Data processing Astronomy / Data processing Datenanalyse (DE-588)4123037-1 gnd Bayes-Verfahren (DE-588)4204326-8 gnd Astronomie (DE-588)4003311-9 gnd |
| topic_facet | Datenverarbeitung Statistical astronomy Statistical astronomy / Data processing Astronomy / Data processing Datenanalyse Bayes-Verfahren Astronomie |
| url | https://doi.org/10.1017/CBO9781316459515 |
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