Hierarchical bayesian modeling code to fit a 4 hyper-parameter binary population model to KPI detections and sensitivity (though applicable to other methods)
Requiers:
astropy
corner
emcee
matplotlib
numpy
scipy
tqdm
Code is split up into two notebooks, the first, binPop.ipynb, takes the detections and sensitivity grids as input and fits a 4 parameter population model using emcee. The second, binPop-figs.ipynb, takes the posterior samples generated in the first notebook and generates pretty figures (seen in Factor & Kraus 2023).