private void NCSSLinRegSlopeDeviation()
{
//NCSS.com Confidence intervals for linear regression slope
var res = Residuals;
var sumsquared = LRM.SumOfSquared(res);
var s = Math.Sqrt(sumsquared / (XValues.Length - 2));
var se = s / Math.Sqrt(LRM.SumOfSquared(XValues));
}
/// <summary>
/// Get fit errors. Returns Tuple(slope error, intercept error).
/// </summary>
/// <returns> </returns>
private Tuple <double, double> GetFittingErrors()
{
if (!IsFitted)
{
return(new Tuple <double, double>(0, 0));
}
var res = Residuals;
var sumofsquared = LRM.SumOfSquared(res);
var ssd = LRM.ArraySumSquareDeviation(XValues);
var oneoverxlength = 1f / (XValues.Length - 2);
var se_slope = Math.Sqrt(oneoverxlength * sumofsquared / ssd);
var se_intercept = se_slope * Math.Sqrt(1f / XValues.Length * LRM.SumOfSquared(XValues));
return(new Tuple <double, double>(se_slope, se_intercept));
}
