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[ascl:1309.005] SATMC: SED Analysis Through Monte Carlo

SATMC is a general purpose, MCMC-based SED fitting code written for IDL and Python. Following Bayesian statistics and Monte Carlo Markov Chain algorithms, SATMC derives the best fit parameter values and returns the sampling of parameter space used to construct confidence intervals and parameter-parameter confidence contours. The fitting may cover any range of wavelengths. The code is designed to incorporate any models (and potential priors) of the user's choice. The user guide lists all the relevant details for including observations, models and usage under both IDL and Python.

Code site:
https://github.com/sethspjohnso/satmc http://dx.doi.org/10.20356/C46P4G
Described in:
http://adsabs.harvard.edu/abs/2013MNRAS.436.2535J
Bibcode:
2013ascl.soft09005J

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ascl:1309.005
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