pastas.modelstats.Statistics.kge_2012
=====================================

.. py:method:: pastas.modelstats.Statistics.kge_2012(tmin: pandas.Timestamp | str | None = None, tmax: pandas.Timestamp | str | None = None, weighted: bool = False, **kwargs) -> float

   
   Kling-Gupta Efficiency.

   :param tmin: A string or pandas.Timestamp with the start date for the period
                (E.g. '1980-01-01 00:00:00'). Strings are converted to pandas.Timestamp
                internally.
   :type tmin: pandas.Timestamp or str, optional
   :param tmax: A string or pandas.Timestamp with the end date for the period
                (E.g. '2020-01-01 00:00:00'). Strings are converted to pandas.Timestamp
                internally.
   :type tmax: pandas.Timestamp or str, optional
   :param weighted: If weighted is True, the variances are computed using the time step
                    between observations as weights. Default is False.
   :type weighted: bool, optional

   .. seealso:: :py:obj:`pastas.stats.kge_2012`















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