Example #1
0
 public IGMNData(IGMN owner, Vector mean)
 {
     this.owner = owner;
     this.gauss = new Gaussian(mean, getStarterCovariance());
     this.inputGauss = new Gaussian(mean.Part(0, mean.Elements.Length - 1), getInputStarterCovariance());
     Age = 1;
     Accumlator = 1;
 }
Example #2
0
        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);
        }