PartitiontoDAG: Sample DAG from partition

In cia: Learn and Apply Directed Acyclic Graphs for Causal Inference

Sample DAG from partition

Description

Samples a DAG in accordance with it's posterior probability conditional on it being consistent with a partition.

Usage

PartitiontoDAG(partitions, scorer)

Arguments

partitions	A cia_chain(s) object or data.frame representing the partition.
scorer	A scorer object.

Value

A cia_chain(s) object or adjacency matrix. For a cia_chain(s) object each state will be an adjacency matrix.

Examples

data <- bnlearn::learning.test

dag <- UniformlySampleDAG(colnames(data))
partition <- DAGtoPartition(dag)

scorer <- CreateScorer(
  scorer = BNLearnScorer, 
  data = data
  )

# Used to sample from a single partition.  
PartitiontoDAG(partition, scorer)

# Used to convert a chain of partitions to DAGs.
results <- SampleChains(3, partition, PartitionMCMC(), scorer)
PartitiontoDAG(results, scorer)

cia documentation built on April 4, 2025, 5:23 a.m.