An efficient Python implementation for Bayesian inference in binary stars based on the probabilistic programming language Stan.
This repository includes the implementation of the statistical models for different binary stellar systems configurations:
- Visual Binary model (
visual.stan). - SB2 model (
sb2.stan). - Visual-SB2 model (
visual_sb2.stan). - Visual-SB1 model (
visual_sb1.stan).
See the examples/Visual_SB2.ipynb notebook for the instructions usage. To incorporate prior distributions see the examples/Visual_SB1_priors.ipynb notebook example.
[1] Videla, M., Mendez, R. A., Claveria, R. M., Silva, J. F., & Orchard, M. E. (2022). Bayesian inference in single-line spectroscopic binaries with a visual orbit. The Astronomical Journal, 163(5).
[2] Carpenter, B., Gelman, A., Hoffman, M. D., Lee, D., Goodrich, B., Betancourt, M., ... & Riddell, A. (2017). Stan: A probabilistic programming language. Journal of statistical software, 76(1).