Ejemplo n.º 1
0
        /// <summary>
        /// Returns a clone of this estimator.
        /// </summary>
        /// <returns></returns>
        public object Clone()
        {
            GaussianEstimator result = new GaussianEstimator();

            result.SetTo(this);
            return(result);
        }
Ejemplo n.º 2
0
        /// <summary>
        /// Initialises the parameters from data
        /// </summary>
        /// <param name="X">X data - initialises weight variances</param>
        public void InitialiseFromData(IList <Vector> X)
        {
            int ND = X.Count;
            int NL = X[0].Count;

            double[] logWeightVariances = new double[NL];

            GaussianEstimator[] gex = new GaussianEstimator[NL];
            for (int l = 0; l < NL; l++)
            {
                gex[l] = new GaussianEstimator();
            }

            for (int d = 0; d < ND; d++)
            {
                Vector x = X[d];
                for (int l = 0; l < NL; l++)
                {
                    gex[l].Add(x[l]);
                }
            }

            double dimMult = System.Math.Sqrt((double)NL);

            for (int l = 0; l < NL; l++)
            {
                Gaussian g      = gex[l].GetDistribution(new Gaussian());
                double   length = 0.5 * dimMult * System.Math.Sqrt(g.GetVariance());

                // If the variance is zero, set to some nominal value.
                // This is different from the situation where length
                // is very small
                if (length < 0.000000001)
                {
                    length = 1.0;
                }

                double wtSDev = 1.0 / length;


                logWeightVariances[l] = 2.0 * System.Math.Log(wtSDev);
            }
            double logBiasWeightVariance = -System.Math.Log((double)NL);

            SetupParams(logWeightVariances, logBiasWeightVariance);
        }
Ejemplo n.º 3
0
 /// <summary>
 /// Sets the state of this estimator from the specified estimator.
 /// </summary>
 /// <param name="value"></param>
 public void SetTo(GaussianEstimator value)
 {
     mva.SetTo(value.mva);
 }