Examples of UncorrelatedRandomVectorGenerator

org.apache.commons.math.random.UncorrelatedRandomVectorGenerator
A {@link RandomVectorGenerator} that generates vectors with uncorrelatedcomponents. Components of generated vectors follow (independent) Gaussian distributions, with parameters supplied in the constructor. @version $Revision: 962515 $ $Date: 2010-07-09 15:15:28 +0200 (ven. 09 juil. 2010) $ @since 1.2
org.apache.commons.math3.random.UncorrelatedRandomVectorGenerator
A {@link RandomVectorGenerator} that generates vectors with uncorrelatedcomponents. Components of generated vectors follow (independent) Gaussian distributions, with parameters supplied in the constructor. @since 1.2

Examples of org.apache.commons.math3.random.UncorrelatedRandomVectorGenerator

            new GaussNewtonOptimizer(true,
                                     new SimpleVectorValueChecker(1.0e-6, 1.0e-6));
        JDKRandomGenerator g = new JDKRandomGenerator();
        g.setSeed(16069223052l);
        RandomVectorGenerator generator =
            new UncorrelatedRandomVectorGenerator(1, new GaussianRandomGenerator(g));
        DifferentiableMultivariateVectorMultiStartOptimizer optimizer =
            new DifferentiableMultivariateVectorMultiStartOptimizer(underlyingOptimizer,
                                                                       10, generator);


        // no optima before first optimization attempt

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Examples of org.apache.commons.math3.random.UncorrelatedRandomVectorGenerator

            new GaussNewtonOptimizer(true,
                                     new SimpleVectorValueChecker(1.0e-6, 1.0e-6));
        JDKRandomGenerator g = new JDKRandomGenerator();
        g.setSeed(12373523445l);
        RandomVectorGenerator generator =
            new UncorrelatedRandomVectorGenerator(1, new GaussianRandomGenerator(g));
        DifferentiableMultivariateVectorMultiStartOptimizer optimizer =
            new DifferentiableMultivariateVectorMultiStartOptimizer(underlyingOptimizer,
                                                                       10, generator);
        optimizer.optimize(100, new DifferentiableMultivariateVectorFunction() {
                public MultivariateMatrixFunction jacobian() {

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Examples of org.apache.commons.math3.random.UncorrelatedRandomVectorGenerator

            new NonLinearConjugateGradientOptimizer(ConjugateGradientFormula.POLAK_RIBIERE,
                                                    new SimpleValueChecker(1.0e-10, 1.0e-10));
        JDKRandomGenerator g = new JDKRandomGenerator();
        g.setSeed(753289573253l);
        RandomVectorGenerator generator =
            new UncorrelatedRandomVectorGenerator(new double[] { 50.0, 50.0 }, new double[] { 10.0, 10.0 },
                                                  new GaussianRandomGenerator(g));
        DifferentiableMultivariateMultiStartOptimizer optimizer =
            new DifferentiableMultivariateMultiStartOptimizer(underlying, 10, generator);
        PointValuePair optimum =
            optimizer.optimize(200, circle, GoalType.MINIMIZE, new double[] { 98.680, 47.345 });

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