示例#1
0
  /** Constructs a new FCI search for the given independence test and background knowledge. */
  public Rfci(IndependenceTest independenceTest) {
    if (independenceTest == null || knowledge == null) {
      throw new NullPointerException();
    }

    this.independenceTest = independenceTest;
    this.variables.addAll(independenceTest.getVariables());
  }
示例#2
0
  /**
   * Constructs a new FCI search for the given independence test and background knowledge and a list
   * of variables to search over.
   */
  public Rfci(IndependenceTest independenceTest, List<Node> searchVars) {
    if (independenceTest == null || knowledge == null) {
      throw new NullPointerException();
    }

    this.independenceTest = independenceTest;
    this.variables.addAll(independenceTest.getVariables());

    Set<Node> remVars = new HashSet<Node>();
    for (Node node1 : this.variables) {
      boolean search = false;
      for (Node node2 : searchVars) {
        if (node1.getName().equals(node2.getName())) {
          search = true;
        }
      }
      if (!search) {
        remVars.add(node1);
      }
    }
    this.variables.removeAll(remVars);
  }
示例#3
0
文件: PcMax.java 项目: renjiey/tetrad
 /**
  * Runs PC starting with a complete graph over all nodes of the given conditional independence
  * test, using the given independence test and knowledge and returns the resultant graph. The
  * returned graph will be a pattern if the independence information is consistent with the
  * hypothesis that there are no latent common causes. It may, however, contain cycles or
  * bidirected edges if this assumption is not born out, either due to the actual presence of
  * latent common causes, or due to statistical errors in conditional independence judgments.
  */
 public Graph search() {
   return search(independenceTest.getVariables());
 }