Package org.jquantlib.math.optimization

Examples of org.jquantlib.math.optimization.NoConstraint$Impl

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        final LevenbergMarquardt solver = new LevenbergMarquardt(ts_.accuracy(), ts_.accuracy(), ts_.accuracy());
        final EndCriteria endCriteria = new EndCriteria(100, 10, 0.00, ts_.accuracy(), 0.00);
        final Constraint solverConstraint = forcePositive_ ? new PositiveConstraint() : new NoConstraint();

        // now start the bootstrapping.
        /*Size*/ final int iInst = localisation_-1;

       
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        final List<Double> yMinExpected_ = new ArrayList<Double>();
        xMinExpected_.add(xMinExpected[xMinExpected.length-1]);
        yMinExpected_.add(xMinExpected[yMinExpected.length-1]);
        costFunctions_.add(new OneDimensionalPolynomDegreeN(coefficients));
        // Set Constraint for optimizers: unconstrained problem
        constraints_.add(new NoConstraint());
        // Set initial guess for optimizer
        final Array initialValue = new Array(0);
        initialValue.add(-100.0);
        initialValues_.add(initialValue);
        // Set end criteria for optimizer
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        final ProjectedCostFunction constrainedSABRError = new ProjectedCostFunction(costFunction, inversedTransformatedGuess, parameterAreFixed);

        final Array projectedGuess = new Array(constrainedSABRError.project(inversedTransformatedGuess));

        final NoConstraint constraint = new NoConstraint();
        final Problem problem = new Problem(constrainedSABRError, constraint, projectedGuess);
        itsCoeffs.SABREndCriteria_ = optMethod_.minimize(problem, endCriteria_);
        final Array projectedResult = new Array(problem.currentValue());
        final Array transfResult = new Array(constrainedSABRError.include(projectedResult));
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