least_squares

SeparableModelResult.least_squares(params=None, **kws)

Least-squares minimization using scipy.optimize.least_squares.

This method wraps scipy.optimize.least_squares, which has inbuilt support for bounds and robust loss functions. By default it uses the Trust Region Reflective algorithm with a linear loss function (i.e., the standard least-squares problem).

Parameters:

• params (Parameters, optional) – Parameters to use as starting point.
• **kws (dict, optional) – Minimizer options to pass to scipy.optimize.least_squares.

Returns:

Object containing the optimized parameter and several goodness-of-fit statistics.

Return type:

MinimizerResult

Changed in version 0.9.0: Return value changed to MinimizerResult.