Bayesian network structure learning
via constraint-based (also known as 'conditional
independence') algorithms.
This package implements the Grow-Shrink (GS)
algorithm, the Incremental Association (IAMB)
algorithm, the Interleaved-IAMB (Inter-IAMB)
algorithm and the Fast-IAMB (Fast-AIMB)
algoirthm.

Bayesian network structure learning
via constraint-based (also known as 'conditional
independence') algorithms.
This package implements the Grow-Shrink (GS)
algorithm, the Incremental Association (IAMB)
algorithm, the Interleaved-IAMB (Inter-IAMB)
algorithm and the Fast-IAMB (Fast-IAMB)
algorithm for both discrete and gaussian networks.
Simulation and some score functions are
implemented for discrete networks.

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
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.

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.

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, simple ad advanced plots)
are also included.