BayesVP: a Bayesian Voigt profile fitting package
  We introduce a Bayesian approach for modeling Voigt profiles in absorption
spectroscopy and its implementation in the python package, BayesVP, publicly
available at https://github.com/cameronliang/BayesVP. The code fits the
absorption line profiles within specified wavelength ranges and generates
posterior distributions for the column density, Doppler parameter, and
redshifts of the corresponding absorbers. The code uses publicly available
efficient parallel sampling packages to sample posterior and thus can be run on
parallel platforms. BayesVP supports simultaneous fitting for multiple
absorption components in high-dimensional parameter space. We provide other
useful utilities in the package, such as explicit specification of priors of
model parameters, continuum model, Bayesian model comparison criteria, and
posterior sampling convergence check.
