bnlearn: Bayesian network structure learning

Bayesian network structure learning via constraint-based (also known as 'conditional independence'), score-based and hybrid algorithms. 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 Hill-Climbing (HC) greedy search algorithm, the Max-Min Hill-Climbing (MMHC) algorithm for both discrete and Gaussian networks, along with many score functions and conditional independence tests. Some utility functions (model comparison and manipulation, random data generation, arc orientation testing, simple and advanced plots) are included, as well as basic parametric and bootstrap inference functions.

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