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-*- texinfo -*-
general linear regression
determine the parameters p_j (j=1,2,...,m) such that the function f(x) = sum_(i=1,...,m) p_j*f_j(x) is the best fit to the given values y_i = f(x_i)
parameters:
return values:
Caution: do NOT request y_var for large data sets, as a n by n matrix is generated
See also (octave)regress, leasqr, nonlin_curvefit, (octave)polyfit, wpolyfit, expfit.