GUEST
Graphical Models in Ultrahigh-Dimensional and Error-Prone Data via Boosting Algorithm
We consider the ultrahigh-dimensional and error-prone data. Our goal aims to estimate the precision matrix and identify the graphical structure of the random variables with measurement error corrected. We further adopt the estimated precision matrix to the linear discriminant function to do classification for multi-label classes.
- Version0.2.0
- R version≥ 3.5.0
- LicenseGPL-2
- Needs compilation?No
- Last release07/30/2024
Documentation
Team
Hui-Shan Tsao
Li-Pang Chen
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Last 30 days
This package has been downloaded 163 times in the last 30 days. Enough downloads to make a small wave in the niche community. The curiosity is spreading! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 6 times.
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Last 365 days
This package has been downloaded 1,998 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was May 22, 2024 with 42 downloads.
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Dependencies
- Imports3 packages
- Suggests1 package