def log_likelihood_css(self, y):
        """
        log likelihood based on conditional sum of squares
        
        Source: http://www.nuffield.ox.ac.uk/economics/papers/1997/w6/ma.pdf

        Parameters
        ----------
        y:
            time series as a DenseVector

        returns log likelihood as a double
        """
        likelihood = self._jmodel.logLikelihoodCSS(_py2java(self._ctx, y))
        return _java2py(self._ctx, likelihood)
def log_likelihood_css ( self , y ) : likelihood = self . _jmodel . logLikelihoodCSS ( _py2java ( self . _ctx , y ) ) return _java2py ( self . _ctx , likelihood )
log likelihood based on conditional sum of squares
        
        Source: http://www.nuffield.ox.ac.uk/economics/papers/1997/w6/ma.pdf

        Parameters
        ----------
        y:
            time series as a DenseVector

        returns log likelihood as a double