generate_graph: Generate a 'caugi' using Erdős-Rényi.

In caugi: Causal Graph Interface

Generate a caugi using Erdős-Rényi.

Description

Sample a random DAG or CPDAG using Erdős-Rényi for random graph generation.

Usage

generate_graph(n, m = NULL, p = NULL, class = c("DAG", "CPDAG"), seed = NULL)

Arguments

n	Integer >= 0. Number of nodes in the graph.
m	Integer in ⁠0, n*(n-1)/2⁠. Number of edges in the graph. Exactly one of m or p must be supplied.
p	Numeric in ⁠[0,1]⁠. Probability of edge creation. Exactly one of m or p must be supplied.
class	"DAG" or "CPDAG". When "CPDAG", the result is the CPDAG (essential graph) of the sampled DAG's Markov equivalence class, returned with class "CPDAG".
seed	Optional integer; random seed for reproducibility.

Value

The sampled caugi object. class = "DAG" returns a "DAG"; class = "CPDAG" returns a "CPDAG".

See Also

Other simulation functions: simulate_data()

Examples

# generate a random DAG with 5 nodes and 4 edges
dag <- generate_graph(n = 5, m = 4, class = "DAG")

# generate a random CPDAG with 5 nodes and edge probability 0.3
cpdag <- generate_graph(n = 5, p = 0.3, class = "CPDAG")

caugi documentation built on Oct. 28, 2026, 1:07 a.m.