['μ_σ = pm.Normal(\'μ_σ\', mu=0, sd=10, shape=8)\n    σ = pm.HalfNormal(\'σ\', sd=1)\n    \n    mu = pm.Normal(\'mu\', mu=μ_σ, sd=σ, shape=8)\n    obs = pm.Normal(\'obs\', mu=mu, sd=sigma, observed=y)\n    \n    idata = pm.sample(1000, tune=1000, chains=4, return_inferencedata=True, idata_kwargs={"log_likelihood": True})\naz.plot_posterior(idata, var_names=[\'μ_σ\', \'σ\']);\naz.plot_posterior(idata, var_names=[\'mu\']);\nplt.show()\n\n']