I am trying to formulate a mixture of Bernoulli for my task. I am unsure how pymc3 handles the p value for this.
My code snippet is:
with dir_model: pi = pm.Dirichlet('pi', a = np.ones(K), shape = K) dri = pm.Dirichlet('dri', a = np.ones((K, B)), shape = (K, B)) category_U = pm.Categorical('category_u', p = pi, shape = B) vector_U = pm.Bernoulli('vec_u', p = dri[category_U], observed = Adj.toarray())
So here p value for
vector_U will be of array shaped
B for each observed value. So how will pymc3 handle this ? I think it will use it as mixture but I am not sure.
Help much appreciated.