/// <summary>
/// Predictive Variance at a given point
/// </summary>
/// <param name="X">Input</param>
/// <returns>Predictive variance</returns>
public double Variance(Vector X)
{
if (IsUniform())
{
Gaussian temp = new Gaussian();
temp.SetToUniform();
return(temp.GetVariance());
}
else
{
Vector kxB = FixedParameters.KernelOf_X_B(X);
return(FixedParameters.Prior.Variance(X) - Beta.QuadraticForm(kxB));
}
}
/// <summary>
/// Predictive distribution at a given point
/// </summary>
/// <param name="X">Input</param>
/// <returns>Predictive distribution</returns>
public Gaussian Marginal(Vector X)
{
if (IsUniform())
{
return(Gaussian.Uniform());
}
else
{
double kxx = FixedParameters.Prior.Variance(X);
Vector kxb = FixedParameters.KernelOf_X_B(X);
Gaussian result = new Gaussian(
kxb.Inner(Alpha) + FixedParameters.Prior.Mean(X), kxx - Beta.QuadraticForm(kxb));
return(result);
}
}