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.

翻译：Bayesian_pyhf是一个Python包，支持对多通道分箱统计模型进行并行贝叶斯与频率学派评估。该工具利用Python库pyhf依据HistFactory框架构建此类模型，该库已包含多种频率学派推断方法。将pyhf构建的模型作为贝叶斯推断的数据生成模型，并通过Python库PyMC进行评估。基于蒙特卡洛链方法，PyMC支持贝叶斯建模，并与arviz库共同提供广泛的贝叶斯分析工具。