rm}(0, 1)\)</span>, then run through the inverse
cumulative distribution function, <span class="math inline">\(y = \mathrm{logit}(u)\)</span>. If this
were not already built in as <code>logistic_rng(0, 1)</code>, it could be
coded in Stan directly as</p>
<pre><code>real standard_logistic_rng() {
  real u = uniform_rng(0, 1);
  real y = logit(u);
  return y;
}</code></pre>
<p>Following the same pattern, a standard normal RNG could be coded as</p>
<pre><code>real standard_normal_rng() {
  real u = uniform_rng