public static IInterpolator1D RegressNotContinuous(double[] Xs, double[] Ys, int nSegments)
{
var nSamples = Xs.Length;
//var x = new double[nSegments + 1];
//var y = new double[nSegments + 1];
var samplesPerSegment = nSamples / nSegments;
var interps = new IInterpolator1D[nSegments];
var uBounds = new double[nSegments];
for (var i = 0; i < nSegments; i++)
{
var sampleXs = Xs.Skip(i * samplesPerSegment).Take(samplesPerSegment).ToArray();
var sampleYs = Ys.Skip(i * samplesPerSegment).Take(samplesPerSegment).ToArray();
var lr = LinearRegression.LinearRegressionVector(sampleXs, sampleYs);
var xLo = sampleXs.First();
var xHi = sampleXs.Last();
var yLo = lr.Alpha + lr.Beta * xLo;
var yHi = lr.Alpha + lr.Beta * xHi;
interps[i] = InterpolatorFactory.GetInterpolator(new[] { xLo, xHi }, new[] { yLo, yHi }, Interpolator1DType.Linear);
uBounds[i] = xHi;
}
uBounds[uBounds.Length - 1] = double.MaxValue;
return(new NonContinuousInterpolator(uBounds, interps));
}
public IInterpolator1D PerformRegression()
{
var nPaths = _pathwiseValuesFwd.Length;
var pathAvgs = _pathwiseValuesFwd.Select(x => x.Average()).ToArray();
if (_pathwiseValuesReg.All(x => x == _pathwiseValuesReg.First()) && pathAvgs.All(x => x == pathAvgs.First()))
{
return(new ParametricLinearInterpolator(pathAvgs.First(), 0.0));
}
var lr = LinearRegression.LinearRegressionVector(_pathwiseValuesReg, pathAvgs);
return(new ParametricLinearInterpolator(lr.Alpha, lr.Beta));
}
public void VectorAndNoneVectorLinearRegressionMatches()
{
var rand = new System.Random();
var xArray = new double[50];
var yArray = new double[50];
for (var i = 0; i < xArray.Length; i++)
{
xArray[i] = rand.NextDouble();
yArray[i] = rand.NextDouble();
}
var reg1 = LinearRegression.LinearRegressionNoVector(xArray, yArray, false);
var reg2 = LinearRegression.LinearRegressionVector(xArray, yArray);
Assert.Equal(reg1.Alpha, reg2.Alpha, 10);
Assert.Equal(reg1.Beta, reg2.Beta, 10);
Assert.Equal(reg1.R2, reg2.R2, 10);
}
public static IInterpolator1D Regress(double[] Xs, double[] Ys, int nSegments)
{
var nSamples = Xs.Length;
var x = new double[nSegments + 1];
var y = new double[nSegments + 1];
var samplesPerSegment = nSamples / nSegments;
for (var i = 0; i < nSegments; i++)
{
var sampleXs = Xs.Skip(i * samplesPerSegment).Take(samplesPerSegment).ToArray();
var sampleYs = Ys.Skip(i * samplesPerSegment).Take(samplesPerSegment).ToArray();
var lr = LinearRegression.LinearRegressionVector(sampleXs, sampleYs);
var xLo = sampleXs.First();
var xHi = sampleXs.Last();
var yLo = lr.Alpha + lr.Beta * xLo;
var yHi = lr.Alpha + lr.Beta * xHi;
if (i == 0)
{
x[0] = xLo;
y[0] = yLo;
x[1] = xHi;
y[1] = yHi;
}
else
{
var xD = sampleXs.Select(q => q - xLo).ToArray();
var yD = sampleYs.Select(q => q - yLo).ToArray();
var lr2 = LinearRegression.LinearRegressionNoIntercept(xD, yD);
var yHiBetter = xD.Last() * lr2.Beta + yLo;
x[i + 1] = xHi;
y[i + 1] = yHiBetter;
}
}
return(InterpolatorFactory.GetInterpolator(x, y, Interpolator1DType.Linear));
}