INTER-IAMB (bnlearn)

Module name	bnlearn_interiamb
Package	bnlearn
Version	4.8.3
Language	R
Docs	here
Paper	Yaramakala and Margaritis[1]
Graph type	DAG
MCMC	No
Edge constraints	Yes
Data type	C, D, M
Data missingness
Intervention type
Docker	bpimages/bnlearn:4.8.3

INTER-IAMB

As in GS, this algorithm is also based on the Markov blanket method to first determine the undirected skeleton. However, in incremental association Markov blanket (inter-IAMB) the variable to be included in the Markov blankets are not considered in static order as in GS and the forward-backward stages are combined into a single procedure, which has the effect of reducing the size of the blankets.

Some fields described

edgeConstraints Name of the JSON file containing background knowledge

Example JSON

[
  {
    "id": "interiamb-zf",
    "alpha": [
      0.01,
      0.05
    ],
    "test": "zf",
    "B": null,
    "maxsx": null,
    "debug": false,
    "undirected": false,
    "timeout": null,
    "edgeConstraints": "edgeConstraints.json"
  },
  {
    "id": "interiamb-mi",
    "alpha": [
      0.01,
      0.05
    ],
    "test": "mi",
    "B": null,
    "maxsx": null,
    "debug": false,
    "undirected": false,
    "timeout": null,
    "edgeConstraints": "edgeConstraints.json"
  }
]