VarianceGammaProcessDiffPCA.java

/*
 * Class:        VarianceGammaProcessDiffPCA
 * Description:  
 * Environment:  Java
 * Software:     SSJ 
 * Copyright (C) 2001  Pierre L'Ecuyer and Universite de Montreal
 * Organization: DIRO, Universite de Montreal
 * @author       
 * @since        2008
 *
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 *
 */
package umontreal.ssj.stochprocess;
 
import umontreal.ssj.rng.*;
import umontreal.ssj.probdist.*;
import umontreal.ssj.randvar.*;

public class VarianceGammaProcessDiffPCA extends VarianceGammaProcessDiff {
   int[] indexEigenUp;
   int[] indexEigenDw;

   public VarianceGammaProcessDiffPCA(double s0, double theta, double sigma, double nu, RandomStream stream) {
      super(s0, theta, sigma, nu, new GammaProcessPCA(0.0, 1.0, 1.0, stream),
            new GammaProcessPCA(0.0, 1.0, 1.0, stream));
      // Params mu, nu of the 2 gamma processes are redefined in init()
      // which will be called after a call to 'setObservTimes'
   }

   public VarianceGammaProcessDiffPCA(double s0, double theta, double sigma, double nu, GammaProcessPCA gpos,
         GammaProcessPCA gneg) {
      super(s0, theta, sigma, nu, gpos, gneg); // from VarianceGammaProcessDiff
      // Params mu, nu of the 2 gamma processes are redefined in init()
      // which will be called after a call to 'setObservTimes'
   }

   public double nextObservation() {
      throw new UnsupportedOperationException("Impossible with PCA, use generatePath() instead.");
   }
 
   public double[] generatePath() {
      double[] u = new double[2 * d];
      for (int i = 0; i < 2 * d; i++)
         u[i] = getStream().nextDouble();
      return generatePath(u);
   }
 
   public double[] generatePath(double[] uniform01) {
      int dd = uniform01.length;
      int d = dd / 2;
 
      if (dd % 2 != 0) {
         throw new IllegalArgumentException("The Array uniform01 must have a even length");
      }
 
      double[] QMCpointsUP = new double[d];
      double[] QMCpointsDW = new double[d];
 
      for (int i = 0; i < d; i++) {
         QMCpointsUP[i] = uniform01[indexEigenUp[i]];
         QMCpointsDW[i] = uniform01[indexEigenDw[i]];
      }
      gpos.resetStartProcess();
      gneg.resetStartProcess();
 
      double[] pathUP = gpos.generatePath(QMCpointsUP);
      double[] pathDOWN = gneg.generatePath(QMCpointsDW);
 
      for (int i = 0; i < d; i++) {
         path[i + 1] = x0 + pathUP[i + 1] - pathDOWN[i + 1];
      }
      observationIndex = d;
      observationCounter = d;
      return path;
   }
 
   protected void init() {
      super.init(); // from VarianceGammaProcessDiff
      if (observationTimesSet) {
         // Two lines below (casts) should be reinstated after fix inheritance
         // PCA/PCABridge.
         double[] eigenValUp = ((GammaProcessPCA) gpos).getBMPCA().getSortedEigenvalues();
         double[] eigenValDw = ((GammaProcessPCA) gneg).getBMPCA().getSortedEigenvalues();
         indexEigenUp = new int[d];
         indexEigenDw = new int[d];
 
         int iUp = 0;
         int iDw = 0;
         for (int iQMC = 0; iQMC < 2 * d; iQMC++) {
            if (iUp == d) {
               indexEigenDw[iDw] = iQMC;
               iDw++;
               continue;
            }
            if (iDw == d) {
               indexEigenUp[iUp] = iQMC;
               iUp++;
               continue;
            }
            if (eigenValUp[iUp] >= eigenValDw[iDw]) {
               indexEigenUp[iUp] = iQMC;
               iUp++;
            } else {
               indexEigenDw[iDw] = iQMC;
               iDw++;
            }
         }
      }
 
   }
 
}