public void RandWishart()
{
// multivariate Gamma
double a = 2.7;
int d = 3;
PositiveDefiniteMatrix mTrue = new PositiveDefiniteMatrix(d, d);
mTrue.SetToIdentity();
mTrue.SetToProduct(mTrue, a);
LowerTriangularMatrix L = new LowerTriangularMatrix(d, d);
PositiveDefiniteMatrix X = new PositiveDefiniteMatrix(d, d);
PositiveDefiniteMatrix m = new PositiveDefiniteMatrix(d, d);
m.SetAllElementsTo(0);
double s = 0;
for (int i = 0; i < nsamples; i++)
{
Rand.Wishart(a, L);
X.SetToProduct(L, L.Transpose());
m = m + X;
s = s + X.LogDeterminant();
}
double sTrue = 0;
for (int i = 0; i < d; i++)
{
sTrue += MMath.Digamma(a - i * 0.5);
}
m.Scale(1.0 / nsamples);
s = s / nsamples;
Console.WriteLine("");
Console.WriteLine("Multivariate Gamma");
Console.WriteLine("-------------------");
Console.WriteLine("m = \n{0}", m);
double dError = m.MaxDiff(mTrue);
if (dError > TOLERANCE)
{
Assert.True(false, String.Format("Wishart({0}) mean: (should be {0}*I), error = {1}", a, dError));
}
if (System.Math.Abs(s - sTrue) > TOLERANCE)
{
Assert.True(false, string.Format("E[logdet]: {0} (should be {1})", s, sTrue));
}
}
public void RandNormalP()
{
double[] m_init = { 1, 2, 3 };
Vector mt = Vector.FromArray(m_init);
double[,] v_init = { { 2, 1, 1 }, { 1, 2, 1 }, { 1, 1, 2 } };
PositiveDefiniteMatrix vt = new PositiveDefiniteMatrix(v_init);
PositiveDefiniteMatrix pt = ((PositiveDefiniteMatrix)vt.Clone()).SetToInverse(vt);
int d = mt.Count;
Vector x = Vector.Zero(d);
VectorMeanVarianceAccumulator mva = new VectorMeanVarianceAccumulator(d);
for (int i = 0; i < nsamples; i++)
{
Rand.NormalP(mt, pt, x);
mva.Add(x);
}
Vector m = mva.Mean;
PositiveDefiniteMatrix v = mva.Variance;
Console.WriteLine("");
Console.WriteLine("Multivariate NormalP");
Console.WriteLine("--------------------");
Console.WriteLine("m = {0}", m);
double dError = m.MaxDiff(mt);
if (dError > TOLERANCE)
{
Assert.True(false, String.Format("m: error = {0}", dError));
}
Console.WriteLine("v = \n{0}", v);
dError = v.MaxDiff(vt);
if (dError > TOLERANCE)
{
Assert.True(false, String.Format("v: error = {0}", dError));
}
}
