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BONNSAI: correlated stellar observables in Bayesian methods

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...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1051/0004-6361/201628409

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Institution:
University of Oxford
Division:
MPLS
Department:
Physics
Sub department:
Astrophysics
Role:
Author
Oxford Centre for Astrophysical Surveys More from this funder
Publisher:
EDP Sciences Publisher's website
Journal:
Astronomy & Astrophysics Journal website
Volume:
598
Article number:
A60
Publication date:
2017-02-01
Acceptance date:
2016-10-06
DOI:
EISSN:
1432-0746
ISSN:
0004-6361
Source identifiers:
681832
Language:
English
Keywords:
Pubs id:
pubs:681832
UUID:
uuid:0bf7cc46-c70f-454a-9778-9797f465e847
Local pid:
pubs:681832
Deposit date:
2017-04-20

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