['μ = pm.Normal(\'μ\', mu=0, sd=10)\n    σ = pm.HalfNormal(\'σ\', sd=10)\n    \n    # Define the likelihood\n    likelihood = pm.Poisson(\'likelihood\', mu=μ + σ, observed=r)\n    \n    # Sample from the posterior\n    trace = pm.sample(1000, tune=1000, chains=4, return_inferencedata=True, idata_kwargs={"log_likelihood": True})\n    \n# Plot the trace and posterior\naz.plot_trace(trace)\nplt.show()\naz.summary(trace, kind=\'stats\', hdi_prob=0.95)\naz.summary(trace, kind=\'stats\', hdi_prob=0.95)\naz.plot_posterior(trace, hdi_prob=0.95)\nplt.show()\naz.plot_posterior(trace, var_names=[\'μ\', \'σ\'], hdi_prob=0.95)\nplt.show()\n\n']