public InstrumentalDistribution(PZMath_vector m, PZMath_matrix s)
{
random = new MultivariateNormalDistribution(m, s);
}
/// <summary>
/// multivariate normal distribution example
/// </summary>
public static void Example()
{
// init a bivariate normal distribution
double[,] D = { { 1.9, 0 },
{ 0, 1.9 } };
double[] m = { 1, 2 };
PZMath_matrix sigam1 = new PZMath_matrix(D);
PZMath_vector mu1 = new PZMath_vector(m);
MultivariateNormalDistribution BND = new MultivariateNormalDistribution(mu1, sigam1);
// sample
string filename1 = "v1.txt";
FileStream fs1 = new FileStream(filename1, FileMode.Create, FileAccess.Write);
StreamWriter w1 = new StreamWriter(fs1);
for (int i = 0; i < 10000; i++)
{
double[] sample = BND.Sample();
w1.Write(sample[0]);
w1.Write(" ");
w1.WriteLine(sample[1]);
}
w1.Close();
fs1.Close();
// evalualte
double[] x = { 1.5, 2.5 };
double value = BND.Evaluate(x);
// correct answer
// value = 0.0734
Console.WriteLine(value);
}
/// <summary>
/// example target distribution function
/// </summary>
/// <param name="x"></param>
/// <returns></returns>
private static double ExampleTargetDistributionFunction(double[] x)
{
//double[,] S = { { 1, 0.9 }, { 0.9, 1 } };
double[,] S = { { 2, 0 }, { 0, 1 } };
double[] m = { 1, 2 };
PZMath_matrix targetSigma = new PZMath_matrix(S);
PZMath_vector targetMu = new PZMath_vector(m);
MultivariateNormalDistribution random = new MultivariateNormalDistribution(targetMu, targetSigma);
return random.Evaluate(x);
}