log likelihood based on conditional sum of squares. In contrast to logLikelihoodCSS the array
        provided should correspond to an already differenced array, so that the function below
        corresponds to the log likelihood for the ARMA rather than the ARIMA process
        
        Parameters
        ----------
        diffedY:
            differenced array as a numpy array
        
        returns log likelihood of ARMA as a double

def log_likelihood_css_arma(self, diffedy):
        """
        log likelihood based on conditional sum of squares. In contrast to logLikelihoodCSS the array
        provided should correspond to an already differenced array, so that the function below
        corresponds to the log likelihood for the ARMA rather than the ARIMA process
        
        Parameters
        ----------
        diffedY:
            differenced array as a numpy array
        
        returns log likelihood of ARMA as a double
        """
        # need to copy diffedy to a double[] for Java
        likelihood =  self._jmodel.logLikelihoodCSSARMA(_py2java_double_array(self._ctx, diffedy))
        return _java2py(self._ctx, likelihood)