Skip to content
forked from jtlz2/bayestack

Flexible, fully bayesian stacking software for modelling of astronomical data sets

License

Notifications You must be signed in to change notification settings

EliabT/bayestack-1

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

bayestack

Please cite:

  • Zwart, Santos and Jarvis (MNRAS 453:1740-1753, 2017)

https://ui.adsabs.harvard.edu/abs/2015MNRAS.453.1740Z/abstract

https://arxiv.org/abs/1503.02493

@ARTICLE{2015MNRAS.453.1740Z,
       author = {{Zwart}, Jonathan T.~L. and {Santos}, Mario and {Jarvis}, Matt J.},
        title = "{Far beyond stacking: fully Bayesian constraints on sub-{\ensuremath{\mu}}Jy radio source populations over the XMM-LSS-VIDEO field}",
      journal = {\mnras},
     keywords = {methods: data analysis, methods: statistical, surveys, galaxies: evolution, radio continuum: galaxies, radio continuum: general, Astrophysics - Cosmology and Nongalactic Astrophysics, Astrophysics - Astrophysics of Galaxies, Astrophysics - Instrumentation and Methods for Astrophysics},
         year = "2015",
        month = "Oct",
       volume = {453},
        pages = {1740-1753},
          doi = {10.1093/mnras/stv1716},
archivePrefix = {arXiv},
       eprint = {1503.02493},
 primaryClass = {astro-ph.CO},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2015MNRAS.453.1740Z},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

Released under GPLv2

Contributors:

  • Jonathan Zwart (jtlz2; author)
  • Song Chen
  • Eliab Malefahlo (maintainer)
  • Catherine Hale
  • Imogen Whittam
  • Mario Santos
  • Matt Jarvis
  • Tessa Vernstrom

Proudly powered by MultiNest (Farhan Feroz and Mike Hobson) and PyMultinest (Johannes Buchner)

About

Flexible, fully bayesian stacking software for modelling of astronomical data sets

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 97.8%
  • C++ 1.6%
  • Other 0.6%