Marginalize and/or condition on variables in an ancestral graph (AG)

Marginalize variables out of an AG, and/or condition on variables. Depending on the structure, it could produce a graph with directed, bidirected, and undirected edges.

Usage

condition_marginalize(cg, cond_vars = NULL, marg_vars = NULL)

Arguments

cg

A caugi ancestral graph of class "AG".

cond_vars

Character vector of nodes to condition on.

marg_vars

Character vector of nodes to marginalize over.

Value

A caugi object of class "AG".

References

Definition 4.2.1 in Thomas Richardson. Peter Spirtes. "Ancestral graph Markov models." Ann. Statist. 30 (4) 962 - 1030, August 2002. doi:10.1214/aos/1031689015

See also

Other operations: dag_from_pdag(), exogenize(), latent_project(), meek_closure(), moralize(), mutate_caugi(), normalize_latent_structure(), skeleton()

Examples

mg <- caugi(
  U %-->% X + Y,
  A %-->% X,
  B %-->% Y,
  class = "DAG"
)

condition_marginalize(mg, marg_vars = "U") # ADMG
#> <caugi object; 4 nodes, 3 edges; simple: TRUE; session=0x555e2abe1880>
#>   graph_class: AG
#>   nodes: A, B, X, Y
#>   edges: A-->X, B-->Y, X<->Y
condition_marginalize(mg, cond_vars = "U") # DAG
#> <caugi object; 4 nodes, 2 edges; simple: TRUE; session=0x555e32fb0d50>
#>   graph_class: AG
#>   nodes: A, B, X, Y
#>   edges: A-->X, B-->Y