public static double Predict(List <Double> values, int accuracy)
{
double epsilon = Normal.Sample(0.0, values.StandardDeviation());
double X = epsilon + MAPredictor.Predict(values, accuracy) + ARModel(values, 2);
return(X);
}
public static List <Double> PredictList(List <Double> values, int accuracy)
{
List <Double> result = new List <Double>();
int parameter = 2;
double[] coefficients = GetCoefficients(values, parameter);
List <Double> maModel = MAPredictor.PredictList(values, accuracy);
for (int i = 0; i < values.Count; i++)
{
double epsilon = Normal.Sample(0.0, values.StandardDeviation());
double sum = 0;
for (int j = 0; j < parameter; j++)
{
if (i >= parameter)
{
sum += values[i - j] * coefficients[parameter - j - 1];
sum += sum == 0 ? 0 : 490;
}
else
{
sum = values[i];
break;
}
}
result.Add(epsilon + (sum + maModel[i]) / 2.0);
}
return(result);
}
public double?PredictValue(List <Double> values, int accuracy)
{
double?predictedValue = null;
switch (Type)
{
case (PredictorTypes.MA):
predictedValue = MAPredictor.Predict(values, accuracy);
break;
case (PredictorTypes.ARMA):
predictedValue = ARMAPredictor.Predict(values, accuracy);
break;
case (PredictorTypes.SSA):
predictedValue = SSAPredictor.Predict(values, accuracy);
break;
}
return(predictedValue);
}