C methods is that the
samples will typically be autocorrelated (or anticorrelated) within a
chain. This increases the uncertainty of the estimation of posterior
quantities of interest, such as means, variances, or quantiles; see
<span class="citation">Geyer (<a href="#ref-Geyer:2011">2011</a>)</span>.</p>
<p>Stan estimates an effective sample size for each parameter, which
plays the role in the Markov chain Monte Carlo central limit theorem
(MCMC CLT) as the number of independent draws plays in the standard