bnlearn: Bayesian network structure learning, parameter learning and
Bayesian network structure learning (via constraint-based, score-based and
hybrid algorithms), parameter learning (via ML and Bayesian estimators) and
This package implements the Grow-Shrink (GS) algorithm, the Incremental Association
(IAMB) algorithm, the Interleaved-IAMB (Inter-IAMB) algorithm, the Fast-IAMB
(Fast-IAMB) algorithm, the Max-Min Parents and Children (MMPC) algorithm, the Hiton-PC
algorithm, the ARACNE and Chow-Liu algorithms, the Hill-Climbing (HC) greedy search
algorithm, the Tabu Search (TABU) algorithm, the Max-Min Hill-Climbing (MMHC)
algorithm and the two-stage Restricted Maximization (RSMAX2) algorithm for both discrete
and Gaussian networks, along with many score functions and conditional independence tests.
The Naive Bayes and the Tree-Augmented Naive Bayes (TAN) classifiers are also implemented.
Some utility functions (model comparison and manipulation, random data generation, arc
orientation testing, simple and advanced plots) are included, as well as support for
parameter estimation and inference, conditional probability queries and cross-validation.