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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.
Version: | 0.2.0 |
Depends: | R (≥ 3.5.0) |
Imports: | XICOR, network, GGally |
Suggests: | sna |
Published: | 2024-07-30 |
DOI: | 10.32614/CRAN.package.GUEST |
Author: | Hui-Shan Tsao [aut, cre], Li-Pang Chen [aut] |
Maintainer: | Hui-Shan Tsao <n410412 at gmail.com> |
License: | GPL-2 |
NeedsCompilation: | no |
CRAN checks: | GUEST results |
Reference manual: | GUEST.pdf |
Package source: | GUEST_0.2.0.tar.gz |
Windows binaries: | r-devel: GUEST_0.2.0.zip, r-release: GUEST_0.2.0.zip, r-oldrel: GUEST_0.2.0.zip |
macOS binaries: | r-release (arm64): GUEST_0.2.0.tgz, r-oldrel (arm64): GUEST_0.2.0.tgz, r-release (x86_64): GUEST_0.2.0.tgz, r-oldrel (x86_64): GUEST_0.2.0.tgz |
Old sources: | GUEST archive |
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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