// Natural spline

        CubicInterpolation f = new CubicInterpolation(

                generic_x, generic_y,

                CubicInterpolation.DerivativeApprox.Spline, false,

                CubicInterpolation.BoundaryCondition.SecondDerivative, generic_natural_y2.last());

        f.update();

        checkValues("Natural spline", f, generic_x, generic_y);

        // cached second derivative

        // Natural spline

        CubicInterpolation f = new CubicInterpolation(

                generic_x, generic_y,

                CubicInterpolation.DerivativeApprox.Spline, false,

                CubicInterpolation.BoundaryCondition.SecondDerivative, generic_natural_y2.last());

        f.update();

        checkValues("Natural spline", f, generic_x, generic_y);

        // cached second derivative

        //Calulating the expected value of the stock quote after time = 18th day from today with the current value of the stock as specified from the quote

        //The expectedValue = intialValue*exp(drift*dt)-----can be obtained by integrating----->dx/x= drift*dt

        final Array expectation = process.expectation(process.time(date18.clone()), new Array(1).fill(5.6), 0.01);

        //Calulating the exact value of the stock quote after time = 18th day from today with the current value of the stock as specified from the quote

        //The exact value = intialValue*exp(drift*dt)*exp(volatility*sqrt(dt))-----can be obtained by integrating----->dx/x= drift*dt+volatility*sqrt(dt)

        final Array evolve = process.evolve(process.time(date18.clone()), new Array(1).fill(6.7), .001, new Array(1).fill(new NormalDistribution().op(Math.random()) ));

        System.out.println("Exact value = "+evolve.first());

        //Calulating the exact value of the stock quote after time = 18th day from today with the current value of the stock as specified from the quote

        //The exact value = intialValue*exp(drift*dt)*exp(volatility*sqrt(dt))-----can be obtained by integrating----->dx/x= drift*dt+volatility*sqrt(dt)

        final Array evolve = process.evolve(process.time(date18.clone()), new Array(1).fill(6.7), .001, new Array(1).fill(new NormalDistribution().op(Math.random()) ));

        //Calculating covariance of the process

        final Matrix covariance = process.covariance(process.time(date18.clone()),  new Array(1).fill(5.6), 0.01);

        System.out.println("Covariance = "+covariance.get(0, 0));

        for(int i = 0; i < f2.size(); i++)

            I += f2.get(i);

        //not sure about this...

        I -= 0.5 * f2.last();

        I *= h;

        return Math.sqrt(I);

    }