Package org.jquantlib.math.matrixutilities

Examples of org.jquantlib.math.matrixutilities.Matrix.mul()


        return diffusion(t, new Array());
    }

    public Matrix covariance(/* @Time */final double t, final Array x) {
        final Matrix sigma = this.diffusion(t, x);
        return sigma.mul(sigma.transpose());
    }

    public Matrix covariance(/* @Time */final double t) {
        return diffusion(t, new Array());
    }
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    }

    @Override
    public Matrix covariance(final /*@Time*/ double t0, final Array x0, final /*@Time*/ double dt)  {
        final Matrix tmp = stdDeviation(t0, x0, dt);
        return tmp.mul(tmp.transpose());
    }

    @Override
    public Array evolve(final /*@Time*/ double t0, final Array x0, final /*@Time*/double dt, final Array dw)  {

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        return diffusion(t, new Array(0)); //ZH:QL097 using Null<Array>
    }

    public Matrix covariance(/* @Time */final double t, final Array x) {
        final Matrix sigma = this.diffusion(t, x);
        return sigma.mul(sigma.transpose());
    }

    public Matrix covariance(/* @Time */final double t) {
        return diffusion(t, new Array(0)); //ZH:QL097 using Null<Array> which is new Array(), see Null.hpp
    }
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    @Override
    public Matrix covarianceDiscretization(
                final StochasticProcess sp,
                /* @Time */final double t0, /* @Real */ final Array x0, /* @Time */final double dt) {
        final Matrix sigma = sp.diffusion(t0, x0);
        return sigma.mul(sigma.transpose()).mulAssign(dt);
    }


    //
    // Implements Discretization1D
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                { 1.0, 2.0, 3.0, 4.0 },
        }, flagsA);

        final Array aD = new Array(new double[] { 1.0, 1.0, 1.0, 1.0 }, flagsB);

        final Array a = mA.mul(aD);
        if (a.size() != mA.rows()) {
            fail("'mul' failed");
        }

        final int offset = a.flags().contains(Address.Flags.FORTRAN) ? 1 : 0;
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    }

    @Override
    public Matrix covariance(final /*@Time*/ double t0, final Array x0, final /*@Time*/ double dt)  {
        final Matrix tmp = stdDeviation(t0, x0, dt);
        return tmp.mul(tmp.transpose());
    }

    @Override
    public Array evolve(final /*@Time*/ double t0, final Array x0, final /*@Time*/double dt, final Array dw)  {

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