public override void HandleNextTick(Tick t)
{
double emaVal = EMA.HandleNextTick(t);
LRValues.Enqueue(emaVal);
double[] Y = LRValues.ToArray();
double stdErr = 0;
if (Y.Count() == X.Length)
{
Vector x_data = new Vector(X);
Vector y_data = new Vector(LRValues.ToArray());
var poly = new PolynomialRegression(x_data, y_data, 2);
for (int i = 0; i < Period; i++)
{
double x = (i);
double y = poly.Fit(x);
stdErr += Math.Pow(LRValues.ToArray()[i] - y, 2);
}
stdErr = Math.Sqrt(stdErr);
}
HighData.Enqueue(EMA[0] + STDEV * stdErr);
MiddleData.Enqueue(EMA[0]);
LowData.Enqueue(EMA[0] - STDEV * stdErr);
}
public override void HandleNextTick(Tick t)
{
MiddleData.Enqueue(MIDDLE.HandleNextTick(t));
var stdev = MIDDLE.ToArray().StandardDeviation();
HighData.Enqueue(MIDDLE[0] + stdev * 2);
LowData.Enqueue(MIDDLE[0] - stdev * 2);
}
public override void HandleNextTick(Tick t)
{
double emaVal = EMA.HandleNextTick(t);
LRValues.Enqueue(emaVal);
double[] Y = LRValues.ToArray();
LinearRegression l = new LinearRegression();
l.Model(Y);
HighData.Enqueue(EMA[0] + STDEV * l.STDERR);
MiddleData.Enqueue(EMA[0]);
LowData.Enqueue(EMA[0] - STDEV * l.STDERR);
}
