KernelDensityVarCorrectGen.java

/*
 * Class:        KernelDensityVarCorrectGen
 * Description:  random variate generators for distributions obtained via
                 kernel density estimation methods
 * Environment:  Java
 * Software:     SSJ 
 * Copyright (C) 2001  Pierre L'Ecuyer and Universite de Montreal
 * Organization: DIRO, Universite de Montreal
 * @author       
 * @since
 *
 *
 * 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.randvar;
 
import umontreal.ssj.probdist.*;
import umontreal.ssj.rng.RandomStream;

public class KernelDensityVarCorrectGen extends KernelDensityGen {
 
   protected double sigmak2; // Value of sigma_k^2.
   protected double mean; // Sample mean of the observations.
   protected double invSigmae; // 1 / sigma_e.

   public KernelDensityVarCorrectGen(RandomStream s, EmpiricalDist dist, RandomVariateGen kGen, double h,
         double sigmak2) {
      super(s, dist, kGen, h);
      this.sigmak2 = sigmak2;
      mean = dist.getSampleMean();
      double var = dist.getSampleVariance();
      invSigmae = 1.0 / Math.sqrt(1.0 + h * h * sigmak2 / var);
   }

   public KernelDensityVarCorrectGen(RandomStream s, EmpiricalDist dist, NormalGen kGen) {
      this(s, dist, kGen, 0.77639 * getBaseBandwidth(dist), 1.0);
   }
 
   public void setBandwidth(double h) {
      if (h < 0)
         throw new IllegalArgumentException("h < 0");
      bandwidth = h;
      double var = ((EmpiricalDist) dist).getSampleVariance();
      invSigmae = 1.0 / Math.sqrt(1.0 + h * h * sigmak2 / var);
   }
 
   public double nextDouble() {
      double x = mean + invSigmae * (dist.inverseF(stream.nextDouble()) - mean + bandwidth * kernelGen.nextDouble());
      if (positive)
         return Math.abs(x);
      else
         return x;
   }
}