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.
|
See Also
