The QUadratic Inverse Covariance algorithm (latest release 1.2)
implements the l1 regularized Gaussian maximum likelihood
estimation of the inverse of a covariance matrix.
We implemented the algorithm in C++ and we provide a MEX package and
an R package released under the GNU General Public License version 3 or
Download the MEX package archive and
extract the files. Compile the program using the provided Makefile or
use the MEX compiler as follows:
> mex -llapack QUIC.C QUIC-mex.C -output QUIC.[mex|mexa64|mexmaci64|...]
The R package is available from CRAN. You can also
download it from here. Install from
within R by issuing:
Please acknowledge the use of the code with a
citation. BibTex records are available for
Sparse Inverse Covariance Matrix Estimation Using Quadratic
Cho-Jui Hsieh, Mátyás A. Sustik, Inderjit S. Dhillon,
Advances in Neural Information Processing Systems, vol. 24, 2011.
Slides from the SAMSI 2012 workshop: [pdf]
Bug reports and comments are
always appreciated. We would like to know who showed interest in our
work, feel free to contact us.
Jun 26, 2015
by Mátyás. Accessed