public double CalcPowerRSquared()
{
if (YVals.Count != 0)
{
var yValMean = YVals.Average();
double totalSumSquares = yVals.Sum(val => Math.Pow((val - yValMean), 2));
//var modelCoeffsRSquared = CalcModelCoeffs(pOrder);
//var modelCoeffsRSquared = CalcLogModelCoeffs();
//var modelCoeffsRSquared = CalcExpModelCoeffs();
var modelCoeffsRSquared = CalcPowerModelCoeffs();
//List<double> calculatedYVals = xVals.Select(x => CalcResultVal(x)).ToList();
//List<double> calculatedYVals = xVals.Select(x => CalcLogResultVal(x)).ToList();
//List<double> calculatedYVals = xVals.Select(x => CalcExpResultVal(x)).ToList();
List <double> calculatedYVals = xVals.Select(x => CalcPowerResultVal(x)).ToList();
double residualSumSquares = 0;
for (var i = 0; i < yVals.Count; i++)
{
residualSumSquares += Math.Pow((YVals[i] - calculatedYVals[i]), 2);
}
var resultVal = 1 - residualSumSquares / totalSumSquares;
return(resultVal >= 0 ? resultVal : 0);
}
return(0);
}
public void Clear()
{
Y2Vals.Clear();
YVals.Clear();
XVals.Clear();
}
//Creates DataPoint objects from the trendline/regression model
public ObservableCollection <Common.DataPoint> CreateRegressionModelDataPoints(Int32 polyOrder)
{
//Recalculate model coefficients to ensure correct regression model
CalcModelCoeffs(polyOrder);
if (polyOrder + 1 != modelCoeffs.Count)
{
return(null);
}
//Determine qty. of returned data points -> Target: 100 data points
var maxXVal = XVals.Max();
var minXVal = XVals.Min();
Int32 dataPointQty = 100;
var stepSize = (maxXVal - minXVal) / dataPointQty;
//Create collection to return
ObservableCollection <DataPoint> calcDataPoints = new ObservableCollection <DataPoint>();
switch (modelCoeffs.Count)
{
//Case of a constant dependent variable
case 1:
if (XVals.Count >= 1)
{
for (int i = 0; i <= dataPointQty; i++)
{
var point = new DataPoint
{
XValue = minXVal + stepSize * i,
YValue = YVals.FirstOrDefault()
};
calcDataPoints.Add(point);
}
return(calcDataPoints);
}
return(null);
//Linear regression model
case 2:
if (XVals.Count >= 2)
{
for (int i = 0; i <= dataPointQty; i++)
{
var point = new DataPoint();
point.XValue = minXVal + stepSize * i;
point.YValue = modelCoeffs[0] + modelCoeffs[1] * point.XValue;
calcDataPoints.Add(point);
}
return(calcDataPoints);
}
return(null);
//Quadratic Regression Model
case 3:
if (XVals.Count >= 3)
{
for (int i = 0; i <= dataPointQty; i++)
{
var point = new DataPoint();
point.XValue = minXVal + stepSize * i;
point.YValue = modelCoeffs[0] + modelCoeffs[1] * point.XValue + modelCoeffs[2] * Math.Pow(point.XValue, 2);
calcDataPoints.Add(point);
}
return(calcDataPoints);
}
return(null);
//3rd Order Polynomial
case 4:
if (XVals.Count >= 4)
{
for (int i = 0; i <= dataPointQty; i++)
{
var point = new DataPoint();
point.XValue = minXVal + stepSize * i;
point.YValue = modelCoeffs[0] + modelCoeffs[1] * point.XValue + modelCoeffs[2] * Math.Pow(point.XValue, 2) + modelCoeffs[3] * Math.Pow(point.XValue, 3);
calcDataPoints.Add(point);
}
return(calcDataPoints);
}
return(null);
//4th Order Polynomial
case 5:
if (XVals.Count >= 5)
{
for (int i = 0; i <= dataPointQty; i++)
{
var point = new DataPoint();
point.XValue = minXVal + stepSize * i;
point.YValue = modelCoeffs[0] + modelCoeffs[1] * point.XValue + modelCoeffs[2] * Math.Pow(point.XValue, 2) + modelCoeffs[3] * Math.Pow(point.XValue, 3) + modelCoeffs[4] * Math.Pow(point.XValue, 4);
calcDataPoints.Add(point);
}
return(calcDataPoints);
}
return(null);
//5th Order Polynomial
case 6:
if (XVals.Count >= 6)
{
for (int i = 0; i <= dataPointQty; i++)
{
var point = new DataPoint();
point.XValue = minXVal + stepSize * i;
point.YValue = modelCoeffs[0] + modelCoeffs[1] * point.XValue + modelCoeffs[2] * Math.Pow(point.XValue, 2) + modelCoeffs[3] * Math.Pow(point.XValue, 3) + modelCoeffs[4] * Math.Pow(point.XValue, 4) + modelCoeffs[5] * Math.Pow(point.XValue, 5);
calcDataPoints.Add(point);
}
return(calcDataPoints);
}
return(null);
}
return(null);
}
