PlotScoreTrace: Plot the score trace

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

Plot the score trace

Description

Plot the score trace

Usage

PlotScoreTrace(
  chains,
  attribute = "log_score",
  n_burnin = 0,
  same_plot = TRUE,
  col = NULL,
  ...
)

Arguments

chains	MCMC chains.
attribute	Name of attribute to plot. Default is "log_score".
n_burnin	Number of steps to remove as burnin.
same_plot	Whether to plot on the same figure or on multiple figures.
col	A string representing a color for a single chain or a vector of strings to cycle through for multiple chains.
...	Extra parameters to pass to the plot and graphics::line functions.

Value

No return value. Called to produce a base R trace plot.

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)

# Plot partition score trace.
PlotScoreTrace(results, type = 'l')

# Plot DAG score trace.
dag_chains <- PartitiontoDAG(results, scorer)
PlotScoreTrace(dag_chains, type = 'l')

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