Bayesian Methodologies with pyhf

2023/09/29 by Feickert, Matthew, Heinrich, Lukas, Horstmann, Malin
#Computation (stat.CO) #FOS: Computer and information sciences #FOS: Physical sciences #High Energy Physics - Experiment (hep-ex)

paper · doi:10.48550/arxiv.2309.17005

Abstract

bayesian_pyhf is a Python package that allows for the parallel Bayesian and frequentist evaluation of multi-channel binned statistical models. The Python library pyhf is used to build such models according to the HistFactory framework and already includes many frequentist inference methodologies. The pyhf-built models are then used as data-generating model for Bayesian inference and evaluated with the Python library PyMC. Based on Monte Carlo Chain Methods, PyMC allows for Bayesian modelling and together with the arviz library offers a wide range of Bayesian analysis tools.

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