Bayesian network structure learning
Description
Bayesian network structure learning
via constraint-based (also known as 'conditional
independence') and score-based 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
and the Hill-Climbing (HC) greedy search
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) are also included.