GUEST

Graphical Models in Ultrahigh-Dimensional and Error-Prone Data via Boosting Algorithm

CRAN Package

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


Insights

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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0 downloadsMar 2, 2025
0 downloadsMar 3, 2025
12 downloadsMar 4, 2025
9 downloadsMar 5, 2025
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6 downloadsMar 21, 2025
3 downloadsMar 22, 2025
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6 downloadsMar 27, 2025
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1 downloadsMar 29, 2025
5 downloadsMar 30, 2025
3 downloadsMar 31, 2025
9 downloadsApr 1, 2025
6 downloadsApr 2, 2025
0 downloadsApr 3, 2025
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0 downloadsApr 5, 2025
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The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

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.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Data provided by CRAN


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Dependencies

  • Imports3 packages
  • Suggests1 package