[
\rho \sim \mathsf{MultiNormal}(0, M).
\]</span></p>
<p><span class="math inline">\(M\)</span> is the Euclidean metric. It can be seen as a transform of parameter space
that makes sampling more efficient; see <span class="citation">Betancourt (<a href="#ref-Betancourt:2017" role="doc-biblioref">2017</a>)</span> for details.</p>
<p>By default Stan sets <span class="math inline">\(M^{-1}\)</span> equal to a diagonal estimate of the
covariance computed during warmup.</p>
</div>
<div id="the-hamiltonian" class