 += log_sum_exp(soft_z[n]);
}</code></pre>
<p>There is an independent standard normal prior on the centroid parameters;
this prior could be swapped with other priors, or even a hierarchical
model to fit an overall problem scale and location.</p>
<p>The only parameter is <code>mu</code>, where <code>mu[k]</code> is the centroid for cluster
<span class="math inline">\(k\)</span>. The transformed parameters <code>soft_z[n]</code> contain the log of the
unnormalized cluster assignment probabilities. The vector 