 satisfying these conditions ensures that <span class="math inline">\(L \, L^{\top}\)</span> is positive semi-definite if <span class="math inline">\(M &gt; N\)</span> and positive definite
if <span class="math inline">\(M = N\)</span>.</p>
<p>A Cholesky factor of a covariance matrix requires <span class="math inline">\(N + \binom{N}{2} + (M - N)N\)</span> unconstrained parameters.</p>
<div id="cholesky-factor-of-covariance-matrix-transform" class="section level3">
<h3 class="unnumbered" number="">Cholesky 