code: ///////////////////////////////////////////////////////////////////////////////
  // For information as to what this class does, see the Javadoc, below.       //
  // Copyright (C) 1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006,       //
  // 2007, 2008, 2009, 2010, 2014, 2015 by Peter Spirtes, Richard Scheines, Joseph   //
  // Ramsey, and Clark Glymour.                                                //
  //                                                                           //
  // This program is free software; you can redistribute it and/or modify      //
  // it under the terms of the GNU General Public License as published by      //
  // the Free Software Foundation; either version 2 of the License, or         //
  // (at your option) any later version.                                       //
  //                                                                           //
  // This program is distributed in the hope that it will be useful,           //
  // but WITHOUT ANY WARRANTY; without even the implied warranty of            //
  // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the             //
  // GNU General Public License for more details.                              //
  //                                                                           //
  // You should have received a copy of the GNU General Public License         //
  // along with this program; if not, write to the Free Software               //
  // Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307  USA //
  ///////////////////////////////////////////////////////////////////////////////
  
  package edu.cmu.tetrad.search;
  
  import edu.cmu.tetrad.data.DataSet;
  import edu.cmu.tetrad.data.ICovarianceMatrix;
  import edu.cmu.tetrad.graph.Node;
  import edu.cmu.tetrad.util.TetradMatrix;
  import org.apache.commons.collections4.map.HashedMap;
  import org.apache.commons.math3.distribution.ChiSquaredDistribution;
  
  import java.util.ArrayList;
  import java.util.Arrays;
  import java.util.List;
  import java.util.Map;
  
  /**
   * Performs a test of conditional independence X _||_ Y | Z1...Zn where all searchVariables are either continuous or discrete.
   * This test is valid for both ordinal and non-ordinal discrete searchVariables.
   *
   * @author Bryan Andrews
   */
  public class IndTestMNLRLRT implements IndependenceTest {
      private DataSet data;
      private Map<Node, Integer> nodesHash;
      private double alpha = 0.001;
  
      // Likelihood function
      private MNLRLikelihood likelihood;
      private boolean verbose = false;
  
  
      // P Values
      private double pValue = Double.NaN;
  
      public IndTestMNLRLRT(DataSet data, double alpha) {
          this.data = data;
          this.likelihood= new MNLRLikelihood(data, -1, 1);
  
          nodesHash = new HashedMap<>();
  
          List<Node> variables = data.getVariables();
  
          for (int i = 0; i < variables.size(); i++) {
              nodesHash.put(variables.get(i), i);
          }
  
          this.alpha = alpha;
      }
  
      /**
       * @return an Independence test for a subset of the searchVariables.
       */
      public IndependenceTest indTestSubset(List<Node> vars) {
          throw new UnsupportedOperationException();
      }
  
      /**
       * @return true if the given independence question is judged true, false if not. The independence question is of the
       * form x _||_ y | z, z = <z1,...,zn>, where x, y, z1,...,zn are searchVariables in the list returned by
       * getVariableNames().
       */
      public boolean isIndependent(Node x, Node y, List<Node> z) {
  
          int _x = nodesHash.get(x);
          int _y = nodesHash.get(y);
          int[] list0 = new int[z.size() + 1];
          int[] list1 = new int[z.size() + 1];
          int[] list2 = new int[z.size()];
          list0[0] = _x;
          list1[0] = _y;
          for (int i = 0; i < z.size(); i++) {
              int _z = nodesHash.get(z.get(i));
              list0[i + 1] = _z;
              list1[i + 1] = _z;
              list2[i] = _z;
          }
  
          double lik_0;
          double dof_0;
          double lik_1;
          double dof_1;
  
          lik_0 = likelihood.getLik(_y, list0) - likelihood.getLik(_y, list2);
          dof_0 = likelihood.getLik(_y, list0) - likelihood.getLik(_y, list2);
  
          lik_1 = likelihood.getLik(_x, list1) - likelihood.getLik(_x, list2);
          dof_1 = likelihood.getLik(_x, list1) - likelihood.getLik(_x, list2);
  
  
          if (dof_0 <= 0) { dof_0 = 1; }
          if (dof_1 <= 0) { dof_1 = 1; }
          double p_0 = 0;
          double p_1 = 0;
          try {
              p_0 = 1.0 - new ChiSquaredDistribution(dof_0).cumulativeProbability(2.0 * lik_0);
          } catch (Exception e) {
              e.printStackTrace();
          }
          try {
              p_1 = 1.0 - new ChiSquaredDistribution(dof_1).cumulativeProbability(2.0 * lik_1);
          } catch (Exception e) {
              e.printStackTrace();
          }
          this.pValue = Math.min(p_0, p_1);
  
          return this.pValue > alpha;
      }
  
      public boolean isIndependent(Node x, Node y, Node... z) {
          List<Node> zList = Arrays.asList(z);
          return isIndependent(x, y, zList);
      }
  
      /**
       * @return true if the given independence question is judged false, true if not. The independence question is of the
       * form x _||_ y | z, z = <z1,...,zn>, where x, y, z1,...,zn are searchVariables in the list returned by
       * getVariableNames().
       */
      public boolean isDependent(Node x, Node y, List<Node> z) {
          return !this.isIndependent(x, y, z);
      }
  
      public boolean isDependent(Node x, Node y, Node... z) {
          List<Node> zList = Arrays.asList(z);
          return isDependent(x, y, zList);
      }
  
      /**
       * @return the probability associated with the most recently executed independence test, of Double.NaN if p value is
       * not meaningful for tis test.
       */
      public double getPValue() {
          return this.pValue;
      }
  
      /**
       * @return the list of searchVariables over which this independence checker is capable of determinining independence
       * relations.
       */
      public List<Node> getVariables() {
          return data.getVariables();
      }
  
      /**
       * @return the list of variable varNames.
       */
      public List<String> getVariableNames() {
          List<Node> variables = getVariables();
          List<String> variableNames = new ArrayList<>();
          for (Node variable1 : variables) {
              variableNames.add(variable1.getName());
          }
          return variableNames;
      }
  
      public Node getVariable(String name) {
          for (int i = 0; i < getVariables().size(); i++) {
              Node variable = getVariables().get(i);
              if (variable.getName().equals(name)) {
                  return variable;
              }
          }
  
          return null;
      }
  
      /**
       * @return true if y is determined the variable in z.
       */
      public boolean determines(List<Node> z, Node y) {
          return false; //stub
      }
  
      /**
       * @return the significance level of the independence test.
       * @throws UnsupportedOperationException if there is no significance level.
       */
      public double getAlpha() {
          return alpha;
      }
  
      /**
       * Sets the significance level.
       */
      public void setAlpha(double alpha) {
          this.alpha = alpha;
      }
  
      public DataSet getData() {
          return data;
      }
  
      @Override
      public ICovarianceMatrix getCov() {
          return null;
      }
  
      @Override
      public List<DataSet> getDataSets() {
          return null;
      }
  
      @Override
      public int getSampleSize() {
          return 0;
      }
  
      @Override
      public List<TetradMatrix> getCovMatrices() {
          return null;
      }
  
      @Override
  
      public double getScore() {
          return getAlpha() - getPValue();
      }
  
      @Override
      public boolean isVerbose() {
          return verbose;
      }
  
      @Override
      public void setVerbose(boolean verbose) {
          this.verbose = verbose;
      }
  }