pastas.solver.least_squares.LeastSquaresBase
============================================

.. toctree::
   :hidden:

   /api/pastas/solver/least_squares/LeastSquaresBase.get_parameter_sample
   /api/pastas/solver/least_squares/LeastSquaresBase.prediction_interval
   /api/pastas/solver/least_squares/LeastSquaresBase.ci_simulation
   /api/pastas/solver/least_squares/LeastSquaresBase.ci_block_response
   /api/pastas/solver/least_squares/LeastSquaresBase.ci_step_response
   /api/pastas/solver/least_squares/LeastSquaresBase.ci_contribution
   /api/pastas/solver/least_squares/LeastSquaresBase.solve
   /api/pastas/solver/least_squares/LeastSquaresBase.fit_report
   /api/pastas/solver/least_squares/LeastSquaresBase.to_dict

.. py:class:: pastas.solver.least_squares.LeastSquaresBase(name: str = 'solver', pcov: pandas.DataFrame | None = None, **kwargs)



   
   Base class for least squares solvers.
















   ..
       !! processed by numpydoc !!

   .. py:property:: pcor
      :type: pandas.DataFrame | None


      
      Property to obtain the parameter correlations from the covariance matrix.

      :returns: **pcor** -- Pandas DataFrame with the correlations for the parameters. If `pcov` is None, returns None.
      :rtype: pandas.DataFrame or None















      ..
          !! processed by numpydoc !!

Methods
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.. autoapisummary::

   pastas.solver.least_squares.LeastSquaresBase.get_parameter_sample
   pastas.solver.least_squares.LeastSquaresBase.prediction_interval
   pastas.solver.least_squares.LeastSquaresBase.ci_simulation
   pastas.solver.least_squares.LeastSquaresBase.ci_block_response
   pastas.solver.least_squares.LeastSquaresBase.ci_step_response
   pastas.solver.least_squares.LeastSquaresBase.ci_contribution
   pastas.solver.least_squares.LeastSquaresBase.solve
   pastas.solver.least_squares.LeastSquaresBase.fit_report
   pastas.solver.least_squares.LeastSquaresBase.to_dict