y
handle Gaussian Processes with multi-variate outputs where only the
output dimensions share a kernel function but vary based on their
scale. If the model allows parameterization in terms of Cholesky
factor of the kernel matrix, this distribution is also more efficient
than <span class="math inline">\(\text{MultiGP}()\)</span>. Note that this function does not take into
account the mean prediction.</p>
</div>
<div id="sampling-statement-50" class="section level3">
<h3><span class="header-section-number">22