GenericLikelihoodModel and fittedvalues

[joep]

GenericLikelihoodModel and its results do not define fittedvalues

Check what minimal methods a subclass has to implement, so we can have some fittedvalues. The meaning of fittedvalues is not obvious in some non-linear or non-normal models.

Is defining a predict method in the model subclass enough? Is there some generic support?

example Markov switching model with AR terms in each state: estimation with GenericLikelihoodModel seems to work fine although it's slow, but how do I get prediction, fitted values and residuals?