Sensitivity and robustness analysis in Bayesian networks with the bnmonitor R package

TL;DR

This paper introduces bnmonitor, an R package designed for validating Bayesian networks, and demonstrates its application through a medical dataset to enhance risk assessment reliability.

Contribution

The paper presents the first comprehensive software tool for Bayesian network validation, filling a gap in existing methods and supporting practical risk assessment.

Findings

bnmonitor provides a wide array of validation functions.

Applied analysis on medical data illustrates its practical utility.

Enhances confidence in Bayesian network-based risk assessments.

Abstract

Bayesian networks are a class of models that are widely used for risk assessment of complex operational systems. There are now multiple approaches, as well as implemented software, that guide their construction via data learning or expert elicitation. However, a constructed Bayesian network needs to be validated before it can be used for practical risk assessment. Here, we illustrate the usage of the bnmonitor R package: the first comprehensive software for the validation of a Bayesian network. An applied data analysis using bnmonitor is carried out over a medical dataset to illustrate the use of its wide array of functions.