{
  matrix[N, N] L;
...
  L = cholesky_decompose(K);
}
parameters {
  vector[N] eta;
}
model {
  eta ~ std_normal();
}
generated quantities {
  vector[N] y;
  y = mu + L * eta;
}</code></pre>
<p>The Cholesky decomposition is only computed once, after the data are
loaded and the covariance matrix <code>K</code> computed. The isotropic
normal distribution for <code>eta</code> is specified as a vectorized
univariate distribution for efficiency; this specifies that each
<code>eta[n]</code> has an independent st