Hierarchical Modeling Labels

Questions
4

Thanks.

I ran the code and it’s been churning for about 3 hours now. To give a little more context, here is my model:

with pm.Model() as sales_model:

    #define the priors
    mu_a = pm.Normal('mu_a', mu = 0, sd = 10)
    sigma_a = pm.HalfCauchy('sigma_a', 5)
    #mu_d = pm.Normal('mu_d', mu = 0, sd = 10)
    #sigma_d = pm.HalfCauchy('sigma_d', 5)


    alpha = pm.Normal('intercept', mu=mu_a, sd = sigma_a, shape = n_dept)
    beta_2 = pm.Normal('IsHoliday_T', mu = 0, sd = 20)
    beta_3 = pm.Normal('Week', mu = 0, sd = 20)

    s = pm.HalfCauchy('sd', 5)

    #define the likelihood
    mu = alpha[dept_idx] + beta_2*train['IsHoliday_True'].values + beta_3*train['Week'].values

    y = pm.StudentT('sales', nu = 5, mu = mu, sd = s
                , observed = train['Weekly_Sales'], shape = train['Weekly_Sales'].shape)

    trace = pm.sample(draws=5000, cores = 1, init = 'advi', progressbar=True)
    print(sales_model.check_test_point())
    trace_plot = pm.traceplot(trace[1000:], grid=True)
    ppc = pm.plot_posterior(trace[1000:])
    summary = pm.summary(trace)
    posterior = pm.trace_to_dataframe(trace)

Here is the arviz code I ran:

import arviz as az
with sales_model:

data = az.from_pymc3(trace=trace, 
                 coords={'departments': dept_names}, 
                 dims={'intercept': ['departments']})

az.plot_trace(data, var_names='intercept')

Is it normal to churn for that long?