sub-.cia_post_chain: Indexing with respect to iterations.
In cia: Learn and Apply Directed Acyclic Graphs for Causal Inference

[.cia_post_chain

R Documentation

Indexing with respect to iterations.

Description

Indexing with respect to iterations.

Usage

## S3 method for class 'cia_post_chain'
x = list()[i, ...]

Arguments

`x`	A cia_post_chain object.
`i`	An index.
`...`	ellipsis for extra indexing parameters.

Value

chain A cia_post_chain.

Examples

data <- bnlearn::learning.test

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

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

results <- SampleChains(10, partitioned_nodes, PartitionMCMC(), scorer)
dag_chains <- PartitiontoDAG(results, scorer)

pedge_sample <- SampleEdgeProbabilities(dag_chains)
pedge_sample[5, ]

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