PlotConcordance: Concordance plot

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

Concordance plot

Description

Plot a concordance plot to compare point-estimates for quantities of interest between chains.

Usage

PlotConcordance(x, ...)

Arguments

x	A list of adjacency matrices representing edge probabilities, a chains object, or a collections object with states as DAGs.
...	Additional parameter to send to the appropriate method. This includes 'highlight' (defauled to 0.3) which sets the cutoff difference that is used to highlight the points, and the probability edge estimation 'method' for a cia_collections object.

Value

A ggplot object or patchwork of ggplot objects.

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, n_parallel_chains = 2)
dags <- PartitiontoDAG(results, scorer)

p_edge <- CalculateEdgeProbabilities(dags)
PlotConcordance(p_edge)

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