- Abstract:
-
In an era of large spectroscopic surveys of stars and big data, sophisticated statistical methods become more and more important in order to infer fundamental stellar parameters such as mass and age. Bayesian techniques are powerful methods because they can match all available observables simultaneously to stellar models while taking prior knowledge properly into account. However, in most cases it is assumed that observables are uncorrelated which is generally not the case. Here, we include c...
Expand abstract - Publication status:
- Published
- Peer review status:
- Peer reviewed
- Version:
- Publisher's version
- Publisher:
- EDP Sciences Publisher's website
- Journal:
- Astronomy & Astrophysics Journal website
- Volume:
- 598
- Pages:
- Article: A60
- Publication date:
- 2017-02-05
- DOI:
- EISSN:
-
1432-0746
- ISSN:
-
0004-6361
- Pubs id:
-
pubs:681832
- URN:
-
uri:0bf7cc46-c70f-454a-9778-9797f465e847
- UUID:
-
uuid:0bf7cc46-c70f-454a-9778-9797f465e847
- Local pid:
- pubs:681832
- Language:
- English
- Keywords:
- Copyright holder:
- ESO
- Copyright date:
- 2017
- Notes:
- Copyright © 2017 ESO.
Journal article
BONNSAI: correlated stellar observables in Bayesian methods
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Oxford Centre for Astrophysical Surveys
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