Examples of BrentMinimizer1D

com.opengamma.analytics.math.minimization.BrentMinimizer1D
ns.apache.org/math/api-2.1/org/apache/commons/math/optimization/univariate/BrentOptimizer.html">Commons Math library implementation of Brent minimization.

Examples of com.opengamma.analytics.math.minimization.BrentMinimizer1D

          chiSqr += FunctionUtils.square((data[i].getBlackVolatility() - _formula.getVolatilityFunction(options[i], forward).evaluate(sabrFormulaData)) / errors[i]);
        }
        return chiSqr;
      }
    };
    final ScalarMinimizer lineMinimizer = new BrentMinimizer1D();
    final ConjugateDirectionVectorMinimizer minimzer = new ConjugateDirectionVectorMinimizer(lineMinimizer, 1e-6, 10000);
    final DoubleMatrix1D fp = transforms.transform(new DoubleMatrix1D(initialFitParameters));
    final DoubleMatrix1D minPos = minimzer.minimize(function, fp);
    final double chiSquare = function.evaluate(minPos);
    final DoubleMatrix1D res = transforms.inverseTransform(minPos);

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Examples of com.opengamma.analytics.math.minimization.BrentMinimizer1D

  }


  public void solveExactFromChiSqTest() {
    final DoubleMatrix1D start = new DoubleMatrix1D(new double[] {1.2, 0.8, -0.2, -0.3 });
    final Function1D<DoubleMatrix1D, Double> f = getChiSqFunction(X, Y, SIGMA, PARAM_FUNCTION);
    final ConjugateGradientVectorMinimizer minimizer = new ConjugateGradientVectorMinimizer(new BrentMinimizer1D());
    final DoubleMatrix1D solution = minimizer.minimize(f, start);
    assertEquals(0.0, f.evaluate(solution), 1e-8);
    assertEquals(1.0, solution.getEntry(0), 1e-8);
    assertEquals(1.0, solution.getEntry(1), 1e-8);
    assertEquals(0.0, solution.getEntry(2), 1e-8);

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Examples of com.opengamma.analytics.math.minimization.BrentMinimizer1D

        final double plenty = getPlenty(data, basisFunction, weightsAndPos, isNormalized);
        return chi2 + 0.0 * plenty; // TODO This is not working with a plenty!!!!
      }
    };


    final ScalarMinimizer lineMinimizer = new BrentMinimizer1D();
    final ConjugateGradientVectorMinimizer minimizer = new ConjugateGradientVectorMinimizer(lineMinimizer, 1e-3, 1000);


        final double[] start = new double[nodePos.size()];
        for (int i = 0; i < start.length; i++) {
          start[i] = VALUE;

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