/// <summary>
/// Compute finite difference coefficients according to the method provided here:
/// http://en.wikipedia.org/wiki/Finite_difference_coefficients
/// </summary>
/// <returns>An array of the coefficients for FD.</returns>
public double[] CreateCoefficients()
{
var result = new double[_pointCount];
var delts = new Matrix(_pointCount, _pointCount);
double[][] t = delts.Data;
for (int j = 0; j < _pointCount; j++)
{
double delt = (j - _center);
double x = 1.0;
for (int k = 0; k < _pointCount; k++)
{
t[j][k] = x / EncogMath.Factorial(k);
x *= delt;
}
}
Matrix invMatrix = delts.Inverse();
double f = EncogMath.Factorial(_pointCount);
for (int k = 0; k < _pointCount; k++)
{
result[k] = (Math
.Round(invMatrix.Data[1][k] * f)) / f;
}
return(result);
}
/// <summary>
/// Calculate G.
/// </summary>
/// <param name="network">The network to calculate for.</param>
/// <param name="e">The event to calculate for.</param>
/// <param name="parents">The parents.</param>
/// <returns>The value for G.</returns>
public double CalculateG(BayesianNetwork network,
BayesianEvent e, IList <BayesianEvent> parents)
{
double result = 1.0;
int r = e.Choices.Count;
var args = new int[parents.Count];
do
{
double n = EncogMath.Factorial(r - 1);
double d = EncogMath.Factorial(CalculateN(network, e,
parents, args) + r - 1);
double p1 = n / d;
double p2 = 1;
for (int k = 0; k < e.Choices.Count; k++)
{
p2 *= EncogMath.Factorial(CalculateN(network, e, parents, args, k));
}
result *= p1 * p2;
} while (EnumerationQuery.Roll(parents, args));
return(result);
}