deal: A Package for Learning Bayesian Networks

Susanne G. Boettcher, Claus Dethlefsen

Main Article Content

Abstract

deal is a software package for use with R. It includes several methods for analysing data using Bayesian networks with variables of discrete and/or continuous types but restricted to conditionally Gaussian networks. Construction of priors for network parameters is supported and their parameters can be learned from data using conjugate updating. The network score is used as a metric to learn the structure of the network and forms the basis of a heuristic search strategy. deal has an interface to Hugin.

Article Details

Article Sidebar