/// <summary>
/// Manage the simulation of the variance gamma process
/// </summary>
/// <param name="Dates">Simulation dates</param>
/// <param name="Noise">Gaussian noise for a single path</param>
/// <param name="OutDynamic">Single path process realization</param>
public void Simulate(double[] Dates, IReadOnlyMatrixSlice Noise, IMatrixSlice OutDynamic)
{
int steps = OutDynamic.R;
double GammaNoise, dt;
OutDynamic[0, 0] = this.s0.fV();
for (int i = 1; i < steps; i++)
{
dt = Dates[i] - Dates[i - 1];
this.gamma = new Fairmat.Statistics.Gamma(dt / this.nu.fV(), 1.0 / this.nu.fV());
GammaNoise = this.gamma.Draw(Engine.Generator);
OutDynamic[i, 0] = OutDynamic[i - 1, 0] * Math.Exp(this.drift * dt +
this.theta.fV() * GammaNoise + this.sigma.fV() * Math.Sqrt(GammaNoise) * Noise[i - 1, 0]);
}
}
/// <summary>
/// Manage the simulation of the variance gamma process
/// </summary>
/// <param name="Dates">Simulation dates</param>
/// <param name="Noise">Gaussian noise for a single path</param>
/// <param name="OutDynamic">Single path process realization</param>
public void Simulate(double[] Dates, IReadOnlyMatrixSlice Noise, IMatrixSlice OutDynamic)
{
int steps = OutDynamic.R;
double GammaNoise, dt;
OutDynamic[0, 0] = this.s0.fV();
for (int i = 1; i < steps; i++)
{
dt = Dates[i] - Dates[i - 1];
this.gamma = new Fairmat.Statistics.Gamma(dt / this.nu.fV(), 1.0 / this.nu.fV());
GammaNoise = this.gamma.Draw(Engine.Generator);
OutDynamic[i, 0] = OutDynamic[i - 1, 0] * Math.Exp(this.drift * dt +
this.theta.fV() * GammaNoise + this.sigma.fV() * Math.Sqrt(GammaNoise) * Noise[i - 1, 0]);
}
}
