AICc Calculation Revised

This version (v1.2.0) revised how MUFASA calculates the AICc relative likelihood to that described by Burnham & Anderson (2004) for least squares estimation with normally distributed errors.

MUFASA's earlier implementation has been shown to be robust through rigorous tests against synthetic spectra (see Chen, M. C-Y. et al. 2020). The improvements brought forward by this version tend to be found in marginal cases where two models provide comparable fits to the data.

First Python 3 Compatible Version

The first Python 3 compatible version release

First pre-release of mufasa

This version of MUFASA is the one used in Chen et al. "Velocity-Coherent Filaments in NGC 1333: Evidence for Accretion Flow?" ApJ (2020; submitted).