ing example involves a bivariate covariance matrix in which the
variances are known, but the covariance is not.</p>
<pre><code>data {
  int&lt;lower=0&gt; N;
  vector[2] y[N];
  real&lt;lower=0&gt; var1;     real&lt;lower=0&gt; var2;
}
transformed data {
  real&lt;lower=0&gt; max_cov = sqrt(var1 * var2);
  real&lt;upper=0&gt; min_cov = -max_cov;
}
parameters {
  vector[2] mu;
  real&lt;lower=min_cov, upper=max_cov&gt; cov;
}
transformed parameters {
  matrix[2, 2] Sigma;
  Sigma[1, 1] = var1;     Sigma[1, 2