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Constrained L1-Minimization for Inverse (Covariance) Matrix Estimation
A robust constrained L1 minimization method for estimating a large sparse inverse covariance matrix (aka precision matrix), and recovering its support for building graphical models. The computation uses linear programming. The method was published in TT Cai, W Liu, X Luo (2011) doi:10.1198/jasa.2011.tm10155.
- Version0.5.0
- R versionunknown
- LicenseGPL-2
- Needs compilation?No
- Last release06/22/2022
Documentation
Team
Xi (Rossi) Luo
T. Tony Cai
Show author detailsRolesAuthorWeidong Liu
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Last 30 days
This package has been downloaded 327 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 26 times.
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Last 365 days
This package has been downloaded 4,420 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Oct 08, 2024 with 51 downloads.
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