TY - JOUR AU - Scutari, Marco PY - 2010/07/16 Y2 - 2024/03/28 TI - Learning Bayesian Networks with the bnlearn R Package JF - Journal of Statistical Software JA - J. Stat. Soft. VL - 35 IS - 3 SE - Articles DO - 10.18637/jss.v035.i03 UR - https://www.jstatsoft.org/index.php/jss/article/view/v035i03 SP - 1 - 22 AB - <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 <b>snow</b> 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). ER -