TrendLine Method
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.
Overload List
| Overload | Description |
|---|---|
| TrendLine(String,Series,Series,Int32) | 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. |
| TrendLine(Series,Series,Int32) | 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. |
| TrendLine(SeriesCollection,Series,Int32) | 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. |
Requirements
Target Platforms: Windows 7, Windows Vista SP1 or later, Windows XP SP3, Windows Server 2008 (Server Core not supported), Windows Server 2008 R2 (Server Core supported with SP1 or later), Windows Server 2003 SP2
See Also