DataModeler

One of the types of objects in Praat. A DataModeler tries to fit N data points (xi, yi) as lying on a particular kind of model function f(x; p) that depends on M parameters p. The parameters p are determined by minimizing the chi squared function χ2(p)=Σ ((yi - f(xi, p))/σi)2, where the sum is over all N data points.

If the individual uncertainties σiof the data are not known before hand, the model parameter are determined by assuming that all uncertainties σ`i` are equal. However an independent assessment of the goodness-of-fit cannot be determined in this case. A good guess for σ2 for this case could be σ2=Σ (yi - f(xi, p))2.

## Drawing