///<summary>
/// VIDYA
///</summary>
///<param name="pNav">Navigator</param>
///<param name="pSource">Field Source</param>
///<param name="periods">Periods</param>
///<param name="R2Scale">R2 Scale</param>
///<param name="Alias">Alias</param>
///<returns>Recordset</returns>
public Recordset VIDYA(Navigator pNav, Field pSource, int periods, double R2Scale, string Alias)
{
int Record;
LinearRegression LR = new LinearRegression();
int RecordCount = pNav.RecordCount;
Field Field1 = new Field(RecordCount, Alias);
Recordset Results = LR.Regression(pNav, pSource, periods);
const int Start = 2;
pNav.Position = Start;
for (Record = Start; Record < RecordCount + 1; Record++)
{
pNav.MovePrevious();
double PreviousValue = pSource.ValueEx(pNav.Position);
pNav.MoveNext();
double R2Scaled = Results.ValueEx("RSquared", pNav.Position) * R2Scale;
Field1.Value(pNav.Position, R2Scaled *
pSource.Value(pNav.Position) + (1 - R2Scaled) * PreviousValue);
pNav.MoveNext();
}//Record
Results.AddField(Field1);
return(Results);
}
private void PlotLinearRegression(List <GPoint> points)
{
var ls = new OxyPlot.Series.LineSeries()
{
MarkerType = ShowMarker ? MarkerType.None : MarkerType.Plus,
MarkerStroke = OxyPlot.OxyColors.Blue
};
LinearFunction func;
if (LinearRegression.Regression(points.ToArray(), out func))
{
int TOTAL = 10;
double x = points.First().X;
double stepX = (points.Last().X - x) / TOTAL;
for (int i = 0; i <= TOTAL; i++)
{
double y = func.Slope * x + func.Intercept;
ls.Points.Add(new OxyPlot.DataPoint(x, y));
x += stepX;
}
ls.Title = $"Linear Regression(R: {func.CorrelationCoeff:f5})";
}
else
{
ls.Title = "Linear Regression(Failed)";
}
base.Series.Add(ls);
}
/// <summary>
/// Action to be executd for calculating indicator
/// </summary>
/// <returns>for future usage. Must be ignored at this time.</returns>
protected override bool TrueAction()
{
// Validate
int iSize = _chartPanel._chartX.RecordCount;
if (iSize == 0)
{
return(false);
}
int paramInt1 = ParamInt(1);
if (paramInt1 < 2 || paramInt1 > iSize / 2)
{
ProcessError("Invalid Periods (min 2) for indicator " + FullName, IndicatorErrorType.ShowErrorMessage);
return(false);
}
// Get the data
string paramStr0 = ParamStr(0);
Field pSource = SeriesToField("Source", paramStr0, iSize);
if (!EnsureField(pSource, paramStr0))
{
return(false);
}
Navigator pNav = new Navigator();
Recordset pRS = new Recordset();
pRS.AddField(pSource);
pNav.Recordset_ = pRS;
// Calculate the indicator
LinearRegression ta = new LinearRegression();
Recordset pInd = ta.Regression(pNav, pSource, paramInt1);
// Output the indicator values
Clear();
for (int n = 0; n < iSize; ++n)
{
AppendValue(DM.TS(n), n < paramInt1 ? null : pInd.Value("RSquared", n + 1));
}
return(_calculateResult = PostCalculate());
}
public double Learn(Vector x, Vector y)
{
//
Random();
aver = y.AverageValue();
var y_ = new Vector(y.Length);
{
y_ = y - aver; disp = Math.Sqrt(y_.Dispersion()); y_ /= disp;
}
if (y_.IsNaN())
{
return(double.NaN);
}
double m = 0.001;
{
var lin = linear.Regression(x, y_); k = linear.k; b = linear.b;
// y_ = y_ - lin;
}
//Calcf(x, y_);
for (int ep = 0; ep < 50; ep++)
{
for (int i = 0; i < 2 * x.Length; i += 1)
{
int ind = (int)(matlib.random.NextDouble() * x.Length);
Train(x[ind], y_[ind], m, m, m);
}
if (m > 5e-5)
{
m /= step;
}
}
double err = 0.0;
for (int i = 0; i < x.Length; i++)
{
err += Math.Abs(G(x[i]) - y_[i]);
}
err /= (double)x.Length;
return(err);
}
///<summary>
/// Time Series Moving Average
///</summary>
///<param name="pNav">Navigator</param>
///<param name="pSource">Field Source</param>
///<param name="periods">Periods</param>
///<param name="Alias">Alias</param>
///<returns>Recordset</returns>
public Recordset TimeSeriesMovingAverage(Navigator pNav, Field pSource, int periods, string Alias)
{
LinearRegression LR = new LinearRegression();
int Record;
int RecordCount = pNav.RecordCount;
Field Field1 = new Field(RecordCount, Alias);
Recordset Results = LR.Regression(pNav, pSource, periods);
pNav.MoveFirst();
for (Record = pNav.Position; Record < RecordCount + 1; Record++)
{
double Value = Results.ValueEx("Forecast", pNav.Position);
Field1.Value(pNav.Position, Value);
pNav.MoveNext();
}
pNav.MoveFirst();
Results.AddField(Field1);
return(Results);
}
