I have a same model and same data for pystan and pyMC3. For pystan, I use optimizing function. For pyMC3, I use
pm.fit(method=“advi”,obj_optimizer = pm.adagrad(learning_rate=0.01),obj_n_mc=25,n=10,random_seed=1)
trace_pars_tmp = ff.sample(1000)
stanmodel.optimizing(iter=1e4,)
The pystan’result is much better(including running time and algorithm accuracy).For pyMC3, what should I do to match pystan optimizaing effect? Thank you.