Penalized MLE of Multi-Layered Gaussian Graphical Models

This is the official code repository for paper titled Penalized Maximum Likelihood Estimation of Multi-Layered Gaussian Graphical Models, published in the Journal of Machine Learning Research, 2016. http://www.jmlr.org/papers/volume17/16-004/16-004.pdf

To cite this work:

@article{Lin2016Penalized,
  author  = {Jiahe Lin and Sumanta Basu and Moulinath Banerjee and George Michailidis},
  title   = {Penalized Maximum Likelihood Estimation of Multi-layered Gaussian Graphical Models},
  journal = {Journal of Machine Learning Research},
  year    = {2016},
  volume  = {17},
  number  = {146},
  pages   = {1--51},
  url     = {http://jmlr.org/papers/v17/16-004.html}
}

For the time being, we provide R implementation of the proposed methodology, which is the one used during model dev. See example.R for a demo.

Notes

I personally found that R env has become a bit difficult to use from a maintainance standpoint (e.g., pkgs no longer being supported by a newer R version), and I plan to roll out a Python version of the algorithm if and only if I find the time, although this may sacrifice some of the options, as certain dependency (e.g., the estimation of a sqrt Lasso) may not necessarily be available.