}_n\)</span> is given by the
posterior standard deviation divided by the square root of the
effective sample size. This standard error is itself estimated as
<span class="math inline">\(\hat{\sigma}_n / \sqrt{N_{\mathrm{eff}}}\)</span>. The smaller the standard
error, the closer the estimate <span class="math inline">\(\hat{\theta}_n\)</span> is expected to be to
the true value. This is just the MCMC CLT applied to an estimator;
see <span class="citation">Geyer (<a href="#ref-Geyer:2011">2011</a>)</span> fo