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> for more details of the MCMC central limit theorem.</p>
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<div id="thinning-samples" class="section level3">
<h3><span class="