BANSHEE–A MATLAB toolbox for Non-Parametric Bayesian Networks

Abstract

Bayesian Networks (BNs) are probabilistic, graphical models for representing complex dependency structures. They have many applications in science and engineering. Their particularly powerful variant – Non-Parametric BNs – are for the first time implemented as an open-access scriptable code, in the form of a MATLAB toolbox “BANSHEE”.1 1 BANSHEE stands for ‘Bayesian Networks in Scholarly Endeavours’. However, a banshee is also, in Irish folklore, a female spirit whose appearance is a warning about impending death. Bayesian Networks have been extensively used in risk analysis in fields ranging from aviation safety through natural hazards to building fire safety, hence they also warn against possible dangers, somewhat similarly to a banshee. The software allows for quantifying the BN, validating the underlying assumptions of the model, visualizing the network and its corresponding rank correlation matrix, and finally making inference with a BN based on existing or new evidence. We also include in the toolbox, and discuss in the paper, some applied BN models published in most recent scientific literature.

Keywords

• Copulas
• Probabilistic models
• Belief Nets