code: def log_likelihood_css(self, y):
          
          likelihood = self._jmodel.logLikelihoodCSS(_py2java(self._ctx, y))
          return _java2py(self._ctx, likelihood)
docs: 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