public void Estimate_ParametersPassed_PiCalculatedAndReturned()
{
const int numberOfStates = 2;
var util = new TestDataUtils();
var observations = util.GetSvcData(util.FTSEFilePath, new DateTime(2010, 12, 18), new DateTime(2011, 12, 18));
var model = HiddenMarkovModelStateFactory.GetState(new ModelCreationParameters <NormalDistribution>()
{
NumberOfStates = numberOfStates, Emissions = CreateEmissions(observations, numberOfStates)
});
model.Normalized = true;
var observationsList = new List <IObservation>();
for (var i = 0; i < observations.Length; i++)
{
observationsList.Add(new Observation(observations[i], i.ToString()));
}
var baseParameters = new BasicEstimationParameters <NormalDistribution> {
Model = model, Observations = Helper.Convert(observations), Normalized = model.Normalized
};
var alphaEstimator = new AlphaEstimator <NormalDistribution>();
var alpha = alphaEstimator.Estimate(baseParameters);
var betaEstimator = new BetaEstimator <NormalDistribution>();
var beta = betaEstimator.Estimate(baseParameters);
var @params = new AdvancedEstimationParameters <NormalDistribution>
{
Alpha = alpha,
Beta = beta,
Observations = observationsList,
Model = model,
Normalized = model.Normalized
};
var gammaEstimator = new GammaEstimator <NormalDistribution>();
var estimator = new PiEstimator();
var parameters = new PiParameters
{
Gamma = gammaEstimator.Estimate(@params),
N = model.N,
Normalized = model.Normalized
};
var estimatedPi = estimator.Estimate(parameters);
Assert.AreEqual(1d, Math.Round(estimatedPi[0] + estimatedPi[1], 5));
}
public void PiEstimator_ParameterPassed_PiEstimatorCreated()
{
var estimator = new PiEstimator();
Assert.IsNotNull(estimator);
}