graphical lasso with known precision matrix structure I wonder if there is a way to estimate the precision matrix when certain elements are restricted to be zero?
Suppose data are from $N(\mu,\Omega)$, where $\Omega=V^{-1}$, i.e. the precision matrix. Suppose we know that $\Omega_{i,j}=0$, $i\neq j\in\{1,2,\dots,p\}$, where $p$ is number of variables. Note, sample size $n$ may be less than $p$.
How do we estimate $\Omega$ when we restrict $\Omega_{i,j}$'s to be zero? Can this be done in R?
I understand that this post has a similar discussion. However, it penalizes $\Omega_{i,j}$ but not set it to be zero.

Would "pathway graphical lasso" be suitable for your case?
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4497513/
