Given a set of data points x[0..ndata-1],y[0..ndata-1] with individual standard deviations sig[0..ndata-1], fit them to a straight line y = a + bx by minimizing ¥ö2. Returned are a,b and their respective probable uncertainties siga and sigb, the chi-square chi2, and the goodness-of-fit probability q (that the fit would have ¥ö2 this large or larger). If mwt=0 on input, then the standard deviations are assumed to be unavailable: q is returned as 1.0 and the normalization of chi2 is to unit standard deviation on all points.
[Visual Basic]
Overloads Public Shared Function TrendLine( _
ByVal s As Series, _
ByVal deviations As Series, _
ByVal mwt As Integer _
) As Series
ForecastEngine Class | ForecastEngine Members | Overload List
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