 \sim \mathsf{normal}(0,10)\)</span>.</p>
<p>On the bottom is an identified model with an improper prior, with
likelihood <span class="math inline">\(y_n \sim \mathsf{normal}(\mu,\sigma)\)</span>. All models
estimate <span class="math inline">\(\mu\)</span> at roughly 0.16 with low Monte Carlo standard
error, but a high posterior standard deviation of 0.1; the true
value <span class="math inline">\(\mu=0\)</span> is within the 90% posterior intervals in all three models.</p>
<p>id:non-identified-stan-fits.f