 inline">\(\sigma=1\)</span>
are well within the posterior 90% intervals.</p></li>
</ul>
<p>The first two points, lack of convergence and hitting the maximum
number of leapfrog steps (equivalently maximum tree depth) are
indicative of improper posteriors. Thus rather than covering up the
problem with poor sampling as may be done with Gibbs samplers,
Hamiltonian Monte Carlo tries to explore the posterior and its failure
is a clear indication that something is amiss in the model.</p>

</div>
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