ey are predicted.</p>
<p>Given <span class="math inline">\(M\)</span> posterior draws from Stan, the sequence <code>log_p[1:M]</code> will be available, so that the log posterior predictive density of the test data given training data and predictors is just <code>log_sum_exp(log_p) - log(M)</code>.</p>
</section>
</section>
<section id="estimation-error" class="level2">
<h2 class="anchored" data-anchor-id="estimation-error">Estimation error</h2>
<section id="parameter-estimates" class="level3 unnumbered">
<