Plot the causal graph of an RCDResult with ggplot2

Draws the estimated causal structure as a ggplot2-based directed graph, like autoplot.LingamResult(). Variable pairs suspected to share a latent confounder (NA entries in the adjacency matrix) are drawn as dashed, arrowless segments.

Usage

# S3 method for class 'RCDResult'
autoplot(
  object,
  threshold = 0,
  node_size = 16,
  node_color = "lightblue",
  label_edges = TRUE,
  label_pos = 0.35,
  ...
)

Arguments

object: Return value of lingam_rcd() (an RCDResult object)
threshold: Coefficients with an absolute value at or below this are not treated as edges (default: 0)
node_size: Node size (default: 16)
node_color: Node fill color (default: "lightblue")
label_edges: Whether to display coefficient labels on edges (default: TRUE)
label_pos: Position of each coefficient label along its edge, as a fraction from the source (0) to the target (1). The default 0.35 places labels off-center (toward the source) so labels on crossing edges do not overlap near the midpoint.
...: Unused

Value

A ggplot object

Examples

# \donttest{
if (requireNamespace("ggplot2", quietly = TRUE) &&
    requireNamespace("igraph", quietly = TRUE)) {
  library(ggplot2)
  confounded <- generate_rcd_sample(n = 300, seed = 1)
  model <- lingam_rcd(confounded$data)
  autoplot(model)
}

# }