JointDistribution Class

[SerializableAttribute]
public class JointDistribution : MultivariateDiscreteDistribution, 
	IFittableDistribution<int[], GeneralDiscreteOptions>, IFittable<int[], GeneralDiscreteOptions>, 
	IFittable<int[]>, IFittableDistribution<int[]>, IDistribution<int[]>, 
	IDistribution, ICloneable, IFittableDistribution<double[]>, IFittable<double[]>, 
	IDistribution<double[]>

<SerializableAttribute>
Public Class JointDistribution
	Inherits MultivariateDiscreteDistribution
	Implements IFittableDistribution(Of Integer(), GeneralDiscreteOptions), 
	IFittable(Of Integer(), GeneralDiscreteOptions), IFittable(Of Integer()), 
	IFittableDistribution(Of Integer()), IDistribution(Of Integer()), 
	IDistribution, ICloneable, IFittableDistribution(Of Double()), IFittable(Of Double()), 
	IDistribution(Of Double())

       x      y      z
a   p(a,x) p(a,y) p(a,z)
b   p(b,x) p(b,y) p(b,z)
c   p(c,x) p(c,y) p(c,z)

// Lets create a joint distribution for two discrete variables:
// the first of which can assume 3 distinct symbol values: 0, 1, 2
// the second which can assume 5 distinct symbol values: 0, 1, 2, 3, 4

int[] symbols = { 3, 5 }; // specify the symbol counts

// Create the joint distribution for the above variables
JointDistribution joint = new JointDistribution(symbols);

// Now, suppose we would like to fit the distribution (estimate
// its parameters) from the following multivariate observations:
// 
double[][] observations = 
{
    new double[] { 0, 0 },
    new double[] { 1, 1 },
    new double[] { 2, 1 },
    new double[] { 0, 0 },
};


// Estimate parameters
joint.Fit(observations);

// At this point, we can query the distribution for observations:
double p1 = joint.ProbabilityMassFunction(new[] { 0, 0 }); // should be 0.50
double p2 = joint.ProbabilityMassFunction(new[] { 1, 1 }); // should be 0.25
double p3 = joint.ProbabilityMassFunction(new[] { 2, 1 }); // should be 0.25

// As it can be seem, indeed {0,0} appeared twice at the data, 
// and {1,1} and {2,1 appeared one fourth of the data each.