Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: Susanne G. Boettcher, Claus Dethlefsen
Title: deal: A Package for Learning Bayesian Networks
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.

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Paper: deal: A Package for Learning Bayesian Networks     Download PDF (Downloads: 26006)
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deal_1.2-4.tar.gz: R source package Download (Downloads: 1414; 66KB)

DOI: 10.18637/jss.v008.i20

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.