The practice of qualitative parameterisation in the development of Bayesian networks

TL;DR

This paper discusses the often-overlooked qualitative parameterisation step in Bayesian network development, which involves a preliminary, qualitative-focused parameter setting to ensure the model's purpose and structure are appropriate before rigorous quantification.

Contribution

It highlights the importance of qualitative parameterisation in Bayesian networks and provides an outline of its role, addressing a gap in the literature.

Findings

Qualitative parameterisation supports model validation and development.

This step is crucial for ensuring the structure is fit for purpose.

It is under-reported despite its importance.

Abstract

The typical phases of Bayesian network (BN) structured development include specification of purpose and scope, structure development, parameterisation and validation. Structure development is typically focused on qualitative issues and parameterisation quantitative issues, however there are qualitative and quantitative issues that arise in both phases. A common step that occurs after the initial structure has been developed is to perform a rough parameterisation that only captures and illustrates the intended qualitative behaviour of the model. This is done prior to a more rigorous parameterisation, ensuring that the structure is fit for purpose, as well as supporting later development and validation. In our collective experience and in discussions with other modellers, this step is an important part of the development process, but is under-reported in the literature. Since the practice focuses on qualitative issues, despite being quantitative in nature, we call this step qualitative parameterisation and provide an outline of its role in the BN development process.