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.cluster.metrics;
  
  import edu.cmu.tetrad.util.TetradVector;
  
  /**
   * Euclidean dissimilarity metric--i.e., the sum of the differences in
   * corresponding variable values.
   *
   * @author Joseph Ramsey
   */
  public class SquaredErrorLoss implements Dissimilarity {
      public double dissimilarity(TetradVector v1, TetradVector v2) {
          if (v1.size() != v2.size()) {
              throw new IllegalArgumentException("Vectors not the same length.");
          }
  
          double sum = 0.0;
  
          for (int j = 0; j < v1.size(); j++) {
              double diff = v1.get(j) - v2.get(j);
              sum += diff * diff;
          }
  
          return sum;
      }
  }
  
  
  
  