qreach

Integer: column position of node in adjacency matrix, of
  which Possible-D-SEP set is to be computed.

Adjacency matrix (coding 0,1,2,3 for no edge, circle,
 arrowhead, tail; e.g., <code>amat[a,b] = 2</code> and <code>amat[b,a] = 3</code>
 implies a -> b)

amat

verbose

Let G be a graph with the following edge types: o-o, o-> or &lt;->, and
 let x be a vertex in the graph. Then this function computes
 Possible-D-SEP(x,G), which is defined as follows: v is in Possible-D-SEP(x,G) iff there is a path p between x and v in G
 such that for every subpath <s,t,u> of p, t is a collider on this
 subpath or <s,t,u> is a triangle in G.</s,t,u></s,t,u> See Spirtes et al (2000) or Definition 3.3 of Colombo et al (2012).

This package contains several functions for causal structure
  learning and causal inference using graphical models. The main algorithms
  for causal structure learning are PC (for observational data without hidden
  variables), FCI and RFCI (for observational data with hidden variables),
  and GIES (for a mix of observational and interventional data without hidden
  variables). For causal inference the IDA algorithm and the generalized
  backdoor criterion is implemented.

qreach: Compute Possible-D-SEP(x,G) of a node x in a PDAG G

Description

Usage

Arguments

Value

References

See Also