public void Initialize()
{
var util = new TestDataUtils();
var msftData = util.GetSvcData(util.MSFTFilePath, new DateTime(2011, 10, 7), new DateTime(2012, 3, 1));
var intlData = util.GetSvcData(util.INTLFilePath, new DateTime(2011, 10, 7), new DateTime(2012, 3, 1));
//var msftData = SecurityDailyDataManager.GetRange("MSFT", new DateTime(2011, 10, 7), new DateTime(2012, 3, 1));
//var nasdaqData = SecurityDailyDataManager.GetRange("^IXIC", new DateTime(2011, 10, 7), new DateTime(2012, 3, 1));
_observations = new List <IObservation>();
_startDistribution = new double[K];
_tpm = new double[K][];
_mixtures = new Mixture <IMultivariateDistribution> [K];
_distributions = new NormalDistribution[K];
_states = new List <IState> {
new State(0, "Stock1"), new State(1, "Stock2")
};
for (var j = 0; j < K; j++)
{
_startDistribution[j] = 1d / K;
}
for (var j = 0; j < K; j++)
{
_tpm[j] = (double[])_startDistribution.Clone();
}
var x = new double[N][];
var y = new double[N][];
for (var i = 0; i < N; i++)
{
_observations.Add(new Observation(msftData[i], i.ToString()));
x[i] = msftData[i]; //new double[] { msftData[i].Open, msftData[i].Low, msftData[i].High, msftData[i].Close };
y[i] = intlData[i]; //new double[] { nasdaqData[i].Open, nasdaqData[i].Low, nasdaqData[i].High, nasdaqData[i].Close };
}
var likelihood = 0.0d;
var d = new NormalDistribution(4);
_distributions[0] = (NormalDistribution)d.Evaluate(x, out likelihood);
_distributions[1] = (NormalDistribution)d.Evaluate(y, out likelihood);
var m = new Mixture <NormalDistribution>(_startDistribution, _distributions);
_mixtures[0] = (Mixture <IMultivariateDistribution>)m.Evaluate(x, out likelihood);
_mixtures[1] = (Mixture <IMultivariateDistribution>)m.Evaluate(x, out likelihood);
}
/// <summary>
/// Trains Gaussian Mixture Model
/// </summary>
/// <param name="observations">Observation matrix</param>
/// <param name="numberOfIterations">Number Of Iterations</param>
public void Train(double[][] observations, int numberOfIterations, double likelihoodTolerance)
{
if (_initialize)
{
Initialize(observations);
}
_mixture = (Mixture <IMultivariateDistribution>)_mixture.Evaluate(observations, out _likelihood);
}