FortesFit: Flexible spectral energy distribution modelling with a Bayesian backbone

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Ada Coda
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FortesFit: Flexible spectral energy distribution modelling with a Bayesian backbone

Post by Ada Coda » Sat Apr 27, 2019 1:52 am

FortesFit: Flexible spectral energy distribution modelling with a Bayesian backbone

Abstract: FortesFit efficiently explores and discriminates between various spectral energy distributions (SED) models of astronomical sources. The Python package adds Bayesian inference to a framework that is designed for the easy incorporation and relative assessment of SED models, various fitting engines, and a powerful treatment of priors, especially those that may arise from non-traditional wave-bands such as the X-ray or radio emission, or from spectroscopic measurements. It has been designed with particular emphasis for its scalability to large datasets and surveys.

Credit: Rosario, D. J.

Site: https://github.com/vikalibrate/FortesFit
http://ui.adsabs.harvard.edu/abs/2018MNRAS.473.5658R

Bibcode: 2019ascl.soft04011R

ID: ascl:1904.011
Last edited by Ada Coda on Sun Apr 28, 2019 7:30 pm, edited 1 time in total.
Reason: Updated code entry.

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