public Gaussian(Vector mean, CovarianceMatrix matrix)
{
this.mean = mean;
this.covariance = matrix;
}
public Gaussian(Vector mean, Vector diagCovariance)
{
this.mean = mean;
covariance = new CovarianceMatrix(diagCovariance);
}
public Gaussian(int dimension)
{
mean = new Vector(dimension);
covariance = new CovarianceMatrix(dimension);
}
public Gaussian(Vector mean)
{
this.mean = mean;
covariance = new CovarianceMatrix(mean.Elements.Length);
}
public void CovarianceMatrixTest()
{
CovarianceMatrix m = new CovarianceMatrix(new Vector(new double[] { 1, 2, 3, 4, 5, 4, 3, 2, 1 }));
m.AddDiad(new Vector(new double[] { 4, 5, 1, 2, 8, 3, 3, 8, 1 }), 0.25);
m.AddDiad(new Vector(new double[] { 8, 3, 3, 1, 2, 8, 1, 4, 5 }), 0.25);
m.MultiplyScalar(3.73871);
m.Covariance.WriteToFile("m.txt");
m.InverseCovariance.WriteToFile("minv.txt");
Console.Out.WriteLine(m.Determinant);
Gaussian g = new Gaussian(new Vector(9), m);
double likelihood = g.Likelihood(new Vector(new double[] { 1, 10, 0, 0, 0, 0, 0, 0, 10 }));
Console.Out.WriteLine(likelihood);
}
