pastas.noisemodels.ArNoiseModel
===============================

.. toctree::
   :hidden:

   /api/pastas/noisemodels/ArNoiseModel.set_init_parameters
   /api/pastas/noisemodels/ArNoiseModel.simulate
   /api/pastas/noisemodels/ArNoiseModel.weights
   /api/pastas/noisemodels/ArNoiseModel.get_correction
   /api/pastas/noisemodels/ArNoiseModel.to_dict

.. py:class:: pastas.noisemodels.ArNoiseModel(name: str = 'noise', norm: bool = True)



   
   Noise model with exponential decay of the residuals and weighting.

   :param name: Name of the noise model. Default is "noise".
   :type name: str, optional
   :param norm: Boolean to indicate whether weights are normalized according to the Von
                Asmuth and Bierkens (2005) paper. Default is True.
   :type norm: boolean, optional

   .. rubric:: Notes

   Calculates the noise :cite:t:`von_asmuth_modeling_2005` according to:

   .. math::

       v(t_1) = r(t_1) - r(t_0) * \exp(- \Delta t / \alpha)

   Calculates the weights as

   .. math::

       w = 1 / \sqrt{(1 - \exp(-2 \Delta t / \alpha))}

   The units of the alpha parameter is always in days. The first value of the noise
   is the residual (:math:`v(t=0=r(t=0)`). First weight is 1 / sig_residuals (i.e.,
   delt = infty). Normalization of weights as in :cite:t:`von_asmuth_modeling_2005`,
   optional.















   ..
       !! processed by numpydoc !!

   .. py:property:: nparam
      :type: int


      
      Number of parameters of the noise model.
















      ..
          !! processed by numpydoc !!

Methods
-------

.. autoapisummary::

   pastas.noisemodels.ArNoiseModel.set_init_parameters
   pastas.noisemodels.ArNoiseModel.simulate
   pastas.noisemodels.ArNoiseModel.weights
   pastas.noisemodels.ArNoiseModel.get_correction
   pastas.noisemodels.ArNoiseModel.to_dict