Fit a polynomial of degree \(n\) to the input signal.

A polynomial \(p(x)=\sum_{i=0}^n p_i x^i=p_0 + p_1 x + p_2 x^2 + … p_n x^n\) of degree \(n\) is fit to the input signal using the method of least squares. That is, the error \(E = \sum_{j=0}^N \left| p(x_j) - f(x_j) \right|^2\) is minimized. In the error expression, \(N\) is the number of samples in the input signal \(f\). The fitted polynomial \(p\) can be subtracted from the original signal \(f\) in order to assess the quality of the fit.

The editor has two options:

Any equidistant signal (see Signal Types ).

The fitted polynomial or the difference between the fitted polynomial and the original signal.