def objective_function(self):
return -float(self.log_likelihood()) - self.log_prior()<EOL>
The objective function for the given algorithm.

This function is the true objective, which wants to be minimized.
Note that all parameters are already set and in place, so you just need
to return the objective function here.

For probabilistic models this is the negative log_likelihood
(including the MAP prior), so we return it here. If your model is not
probabilistic, just return your objective to minimize here!