### Kim-Chuan Toh and Lu Li

The software was first released in 2011. The software is designed to solve sparse inverse covariance selection problems of the form:

$$\qquad \min_X \big\{ {\rm Trace}(S X) - {\rm logdet}(X) + \sum_{(i,j)\not\in E} H_{ij} |X_{ij}| \mid X_{ij} = 0 \;\forall\; (i,j) \in E,\, X \succeq 0 \big\}$$

where $$S$$ is the given data, $$H_{ij}$$ are given positive weights, and $$E$$ is a given set of index pairs.
Important note: this is a research software. It is not intended nor designed to be a general purpose software at the moment.
Citation:
• Lu Li and Kim-Chuan Toh An inexact interior point method for L1-regularized sparse covariance selection, Mathematical Programming Computation, 2 (2010), pp. 291--315.

• Copyright: This version of SPINCOVSE is distributed under the GNU General Public License 2.0. For commercial applications that may be incompatible with this license, please contact the authors to discuss alternatives.
• Download SPINCOVSE-0.zip. The package also contains data tested in the above paper.
Please read. Welcome to SPINCOVSE-0! The software requires a few Mex files for execution. You can generate (only need to be done once) these Mex files as follows:
• Firstly, unpack the software:
unzip SPINCOVSE-0.zip
• Run Matlab in the directory SPINCOVSE-0
• In the Matlab command window, type:
>> Installmex
• After that, to see whether you have installed SPINCOVSE-0 correctly, type:
>> startup
>> runexpt_ar
• By now, SPINCOVSE is ready for you to use.