pastas.typing.types.ModelSettingsDict
=====================================

.. py:class:: pastas.typing.types.ModelSettingsDict



   
   Model settings dictionary defining logic for handling time series and model fitting.

   :param tmin: A pandas.Timestamp with the start date for the simulation period
                (E.g. '1980-01-01 00:00:00'). If none is provided, the tmin from
                the oseries is used.
   :type tmin: pandas.Timestamp
   :param tmax: A pandas.Timestamp with the end date for the simulation period
                (E.g. '2020-01-01 00:00:00'). If none is provided, the tmax from
                the oseries is used.
   :type tmax: pandas.Timestamp
   :param freq: String with the frequency the stressmodels are simulated. Must be one of
                the following: (D, h, m, s, ms, us, ns) or a multiple of that e.g. "7D".
   :type freq: str
   :param warmup: Warmup period (in days) for which the simulation is calculated, but not
                  used for the calibration period.
   :type warmup: Timedelta
   :param fit_constant: Argument that determines if the constant is fitted as a parameter. If it
                        is set to False, the constant is set equal to the mean of the residuals.
   :type fit_constant: bool, optional
   :param freq_obs: String with the frequency of the observations that the model will be
                    calibrated on. Must be one of the following (D, h, m, s, ms, us, ns) or a
                    multiple of that e.g. "7D". Should generally be larger than the frequency
                    of the original observations and the model frequency (freq). If freq_obs
                    is None, the frequency of the model (freq) will be used.
   :type freq_obs: str, optional















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