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///////////////////////////////////////////////////////////////////////////////
// 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, 2022 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         //
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// GNU General Public License for more details.                              //
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package edu.cmu.tetrad.sem;

import edu.cmu.tetrad.calculator.expression.Context;
import edu.cmu.tetrad.calculator.expression.Expression;
import edu.cmu.tetrad.graph.Node;
import org.apache.commons.math3.distribution.RealDistribution;

import java.util.ArrayList;
import java.util.List;

/**
 * Returns a sample empirical distribution for a particular expression.
 *
 * @author josephramsey
 * @version $Id: $Id
 */
public class EmpiricalDistributionForExpression {
    private final GeneralizedSemPm semPm;
    private final Node error;
    private final Context context;

    /**
     * 

Constructor for EmpiricalDistributionForExpression.

* * @param semPm a {@link edu.cmu.tetrad.sem.GeneralizedSemPm} object * @param error a {@link edu.cmu.tetrad.graph.Node} object * @param context a {@link edu.cmu.tetrad.calculator.expression.Context} object */ public EmpiricalDistributionForExpression(GeneralizedSemPm semPm, Node error, Context context) { this.semPm = semPm; this.error = error; this.context = context; } /** *

getDist.

* * @return a {@link org.apache.commons.math3.distribution.RealDistribution} object */ public RealDistribution getDist() { List drawFromDistribution = new ArrayList<>(); Expression expression = this.semPm.getNodeExpression(this.error); for (int k = 0; k < 5000; k++) { double evaluate = expression.evaluate(this.context); drawFromDistribution.add(evaluate); } return new EmpiricalCdf(drawFromDistribution); } }




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