Calculates an approximation to the Akaike Information Criterion (AIC). This is an approximation
        as we use the conditional likelihood, rather than the exact likelihood. Please see
        [[https://en.wikipedia.org/wiki/Akaike_information_criterion]] for more information on this
        measure.
        
        Parameters
        ----------
        ts:
            the timeseries to evaluate under current model
            
        Returns an approximation to the AIC under the current model as a double

def approx_aic(self, ts):
        """
        Calculates an approximation to the Akaike Information Criterion (AIC). This is an approximation
        as we use the conditional likelihood, rather than the exact likelihood. Please see
        [[https://en.wikipedia.org/wiki/Akaike_information_criterion]] for more information on this
        measure.
        
        Parameters
        ----------
        ts:
            the timeseries to evaluate under current model
            
        Returns an approximation to the AIC under the current model as a double
        """
        return self._jmodel.approxAIC(_py2java(self._ctx, Vectors.dense(ts)))