'Loglikelihood evaluation
Parameters
params : array_like
Array of parameters at which to evaluate the loglikelihood
function.
transformed : boolean, optional
Whether or not `params` is already transformed. Default is True.
**kwargs
Additional keyword arguments to pass to the Kalman filter. See
`KalmanFilter.filter` for more details.
Notes
[1]_ recommend maximizing the average likelihood to avoid scale issues;
this is done automatically by the base Model fit method.
References
.. [1] Koopman, Siem Jan, Neil Shephard, and Jurgen A. Doornik. 1999.
Statistical Algorithms for Models in State Space Using SsfPack 2.2.
Econometrics Journal 2 (1): 107-60. doi:10.1111/1368-423X.00023.
See Also
update : modifies the internal state of the Model to reflect new params'

def loglikeobs(self, params, transformed=True, complex_step=False, **kwargs):

    if (not transformed):
        params = self.transform_params(params)
    if complex_step:
        kwargs['inversion_method'] = (INVERT_UNIVARIATE | SOLVE_LU)
    self.update(params, transformed=True, complex_step=complex_step)
    return self.ssm.loglikeobs(complex_step=complex_step, **kwargs)
