Technical properties of Ranked Nodes Method

TL;DR

This paper analyzes the ranked nodes method (RNM) for constructing Bayesian network tables, providing analytical and experimental insights mainly for cases with parent and child nodes sharing the same ordinal states.

Contribution

It offers new analytical and experimental results on RNM, highlighting properties useful for its future development in Bayesian network modeling.

Findings

RNM properties support future elaboration

Results focus on nodes with identical ordinal states

Analytical and experimental validation of RNM

Abstract

This paper presents analytical and experimental results on the ranked nodes method (RNM) that is used to construct conditional probability tables for Bayesian networks by expert elicitation. The majority of the results are focused on a setting in which RNM is applied to a child node and parent nodes that all have the same amount discrete ordinal states. The results indicate on RNM properties that can be used to support its future elaboration and development.