pastas.stats.metrics.bic
========================

.. py:function:: pastas.stats.metrics.bic(obs: pandas.Series | None = None, sim: pandas.Series | None = None, res: pandas.Series | None = None, missing: str = 'drop', nparam: int = 1) -> float

   
   Compute the Bayesian Information Criterium (BIC).

   :param obs: Series with the observed values.
   :type obs: pandas.Series, optional
   :param sim: The Series with the simulated values.
   :type sim: pandas.Series, optional
   :param res: The Series with the residual values. If time series for the residuals are
               provided, the sim and obs arguments are ignored. Note that the residuals
               must be computed as `obs - sim` here.
   :type res: pandas.Series, optional
   :param nparam: number of calibrated parameters.
   :type nparam: int, optional
   :param missing: string with the rule to deal with missing values. Only "drop" is supported now.
   :type missing: str, optional

   .. rubric:: Notes

   The Bayesian Information Criterium (BIC) :cite:p:`akaike_bayesian_1979` is
   computed as follows:

   .. math:: \text{BIC} = -2 log(L) + n_{param} * log(N)

   where :math:`n_{param}` is the number of calibration parameters.















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