Examples of RombergIntegrator

org.apache.commons.math.analysis.integration.RombergIntegrator
orld.wolfram.com/RombergIntegration.html"> Romberg Algorithm for integration of real univariate functions. For reference, see Introduction to Numerical Analysis, ISBN 038795452X, chapter 3.
Romberg integration employs k successive refinements of the trapezoid rule to remove error terms less than order O(N^(-2k)). Simpson's rule is a special case of k = 2.
@version $Revision: 1070725 $ $Date: 2011-02-15 02:31:12 +0100 (mar. 15 févr. 2011) $ @since 1.2
org.apache.commons.math3.analysis.integration.RombergIntegrator
orld.wolfram.com/RombergIntegration.html"> Romberg Algorithm for integration of real univariate functions. For reference, see Introduction to Numerical Analysis, ISBN 038795452X, chapter 3.
Romberg integration employs k successive refinements of the trapezoid rule to remove error terms less than order O(N^(-2k)). Simpson's rule is a special case of k = 2.
@since 1.2

Examples of org.apache.commons.math.analysis.integration.RombergIntegrator

      lastJ = j;
    }
    k[k.length - 1] = n - lastJ;


    // now verify probabilities by comparing to integral of pdf
    UnivariateRealIntegrator integrator = new RombergIntegrator();
    for (int i = 0; i < xs.length - 1; i++) {
      double delta = integrator.integrate(new UnivariateRealFunction() {
        public double value(double v) {
          return dist.pdf(v);
        }
      }, xs[i], xs[i + 1]);
      Assert.assertEquals(delta, p[i + 1], 1.0e-6);

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Examples of org.apache.commons.math.analysis.integration.RombergIntegrator

      lastJ = j;
    }
    k[k.length - 1] = n - lastJ;


    // now verify probabilities by comparing to integral of pdf
    UnivariateRealIntegrator integrator = new RombergIntegrator();
    for (int i = 0; i < xs.length - 1; i++) {
      double delta = integrator.integrate(new UnivariateRealFunction() {
        @Override
        public double value(double v) {
          return dist.pdf(v);
        }
      }, xs[i], xs[i + 1]);

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Examples of org.apache.commons.math3.analysis.integration.RombergIntegrator

      lastJ = j;
    }
    k[k.length - 1] = n - lastJ;


    // now verify probabilities by comparing to integral of pdf
    UnivariateIntegrator integrator = new RombergIntegrator();
    for (int i = 0; i < xs.length - 1; i++) {
      double delta = integrator.integrate(1000000, new UnivariateFunction() {
        @Override
        public double value(double v) {
          return dist.pdf(v);
        }
      }, xs[i], xs[i + 1]);

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Examples of org.apache.commons.math3.analysis.integration.RombergIntegrator


                    public double value(final double x) {
                        return x * density(x);
                    }
                };
                final UnivariateIntegrator integrator = new RombergIntegrator();
                return integrator.integrate(Integer.MAX_VALUE, f, x0, x4);
            }


            public double getNumericalVariance() {
                final double meanX = getNumericalMean();
                final UnivariateFunction f = new UnivariateFunction() {


                    public double value(final double x) {
                        return x * x * density(x);
                    }
                };
                final UnivariateIntegrator integrator = new RombergIntegrator();
                final double meanX2 = integrator.integrate(Integer.MAX_VALUE,
                        f, x0, x4);
                return meanX2 - meanX * meanX;
            }


            public double getSupportLowerBound() {

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Examples of org.apache.commons.math3.analysis.integration.RombergIntegrator

      final double freq = 1d / 3600d;
      final double min = 0;// j * .10d;
      final SineIntensity intensity = new SineIntensity(
          1d, freq, relHeight, min);


      final UnivariateIntegrator ri = new RombergIntegrator(16, 32);// new
      // TrapezoidIntegrator();//
      // new
      // SimpsonIntegrator();//
      // new
      // RombergIntegrator();


      final double val = ri.integrate(10000000, new IntensityFunctionWrapper(
          intensity), 0, lengthOfScenario);
      System.out
          .printf("%1d relative height: %1.3f%n", i, relHeight);


      final double newAmpl = orders / val;


      final SineIntensity finalIntensity = new SineIntensity(
          newAmpl, freq, relHeight, newAmpl * min);
      final double compensatedArea = ri.integrate(10000000,
          new IntensityFunctionWrapper(
              finalIntensity), 0, lengthOfScenario);
      // System.out.printf("compensated area: %1.3f%n", compensatedArea);


      final List<Double> sineTimes = FluentIterable

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Examples of org.apache.commons.math3.analysis.integration.RombergIntegrator


                    public double value(final double x) {
                        return x * density(x);
                    }
                };
                final UnivariateIntegrator integrator = new RombergIntegrator();
                return integrator.integrate(Integer.MAX_VALUE, f, x0, x4);
            }


            public double getNumericalVariance() {
                final double meanX = getNumericalMean();
                final UnivariateFunction f = new UnivariateFunction() {


                    public double value(final double x) {
                        return x * x * density(x);
                    }
                };
                final UnivariateIntegrator integrator = new RombergIntegrator();
                final double meanX2 = integrator.integrate(Integer.MAX_VALUE,
                        f, x0, x4);
                return meanX2 - meanX * meanX;
            }


            public double getSupportLowerBound() {

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