quires the first step of the
covariance matrix transform, namely log transforming the positive
diagonal elements. Suppose <span class="math inline">\(x\)</span> is an <span class="math inline">\(M \times N\)</span> Cholesky factor.
The above-diagonal entries are zero, the diagonal entries are
positive, and the below-diagonal entries are unconstrained. The
transform required is thus</p>
<p><span class="math display">\[
y_{m,n} =
\left\{
\begin{array}{cl}
0 &amp; \mbox{if } m &lt; n,
\\
\log x_{m,m} &amp; \mb