pan>,0);
n = 10;
N = 100;
Strue = sprandsym(n,0.5,0.01,1);
nnz_true = sum(Strue(:)&gt;1e-4);
R = inv(full(Strue));
y_sample = sqrtm(R)*randn(n,N);
Y = cov(y_sample');
Nlambda = 20;
lambda = logspace(-2, 3, Nlambda);
nnz = zeros(1,Nlambda);

<span class="keyword">for</span> i=1:Nlambda
    disp([<span class="string">'i = '</span> num2str(i) <span class="string">', lambda(i) = '</span> num2str(lambda(i))]);
    <span class="comment">% Maximum likelihood estimate of R^{-1}</span>
    cvx_begin <span class="str