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else:
#Dirichlet distribution returns a valid pmf over n_covariates statesv_0=self.original_data.rng.dirichlet(np.ones(data.n_covariates), size=1)
ifpen=="auto":
#if pen =="auto", we have an additional parameter to optimize over, so we append itv_0=np.append(v_0, self.original_data.rng.lognormal(1.5, 1, size=1)) #Still experimenting with what distribution is appropriate
The text was updated successfully, but these errors were encountered:
run code below , get the error "ValueError: 'x0' must only have one dimension."
maybe optimize.py should delete "size=1"?
The text was updated successfully, but these errors were encountered: