Learning Bayesian Networks with the bnlearn R Package

Learning Bayesian Networks with the bnlearn R Package

<b>bnlearn</b> is an <b>R</b> package (R Development Core Team 2010) which includes several algorithms for learning the structure of Bayesian networks with either discrete or continuous variables. Both constraint-based and score-based algorithms are implemented, and can use t...

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Bibliographic Details
Main Author: Marco Scutari
Format: Article
Language:English
Published: Foundation for Open Access Statistics 2010-10-01
Series:Journal of Statistical Software
Subjects:
bayesian networks
R
structure learning algorithms
constraint-based algorithms
score-based algorithms
conditional independence tests
Online Access:http://www.jstatsoft.org/v35/i03/paper
Description
Summary:<b>bnlearn</b> is an <b>R</b> package (R Development Core Team 2010) which includes several algorithms for learning the structure of Bayesian networks with either discrete or continuous variables. Both constraint-based and score-based algorithms are implemented, and can use the functionality provided by the snow package (Tierney et al. 2008) to improve their performance via parallel computing. Several network scores and conditional independence algorithms are available for both the learning algorithms and independent use. Advanced plotting options are provided by the <b>Rgraphviz</b> package (Gentry et al. 2010).
ISSN:1548-7660

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