Closed YoelPH closed 7 months ago
True, this is a problem for sampling.
However, the proposed solution would limit all parameters of any distribution to be between 0 and 1. Instead, I now delegated the responsibility to define parameter bounds to the user who defines the parametric function: It should raise a ValueError
(as it should anyways) when invalid parameters are provided. This exception is the propagated in the set_params()
method and eventually leads the likelihood()
method to return -np.inf
.
Do you think that solution will work?
There is an issue when sampling since NaN values are produced in the likelihood. I pinned down the problem to the diagnose time file.
in line 188 we have:
which means that we do not check whether the parameter is in an allowed range. I exchanged it with: