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Multivariate estimation and testing, currently a package for testing parametric data. To deal with parametric data, various multivariate normality tests and outlier detection are performed and visualized using the 'ggplot2' package. Homogeneity tests for covariance matrices are also possible, as well as the Hotelling's T-square test and the multivariate analysis of variance test. We are exploring additional tests and visualization techniques, such as profile analysis and randomized complete block design, to be made available in the future and making them easily accessible to users.
Version: | 0.1.0 |
Depends: | R (≥ 3.5.0) |
Imports: | stats, ggplot2 (≥ 3.4.0), gridExtra (≥ 2.3) |
Suggests: | testthat (≥ 3.0.0) |
Published: | 2024-06-06 |
DOI: | 10.32614/CRAN.package.MVET |
Author: | Yeonseok Choi [aut, cre], Yong-Seok Choi [ctb] |
Maintainer: | Yeonseok Choi <yeonseok3488 at gmail.com> |
License: | MIT + file LICENSE |
URL: | https://github.com/YeonSeok-Choi/MVET |
NeedsCompilation: | no |
CRAN checks: | MVET results |
Reference manual: | MVET.pdf |
Package source: | MVET_0.1.0.tar.gz |
Windows binaries: | r-devel: MVET_0.1.0.zip, r-release: MVET_0.1.0.zip, r-oldrel: MVET_0.1.0.zip |
macOS binaries: | r-release (arm64): MVET_0.1.0.tgz, r-oldrel (arm64): MVET_0.1.0.tgz, r-release (x86_64): MVET_0.1.0.tgz, r-oldrel (x86_64): MVET_0.1.0.tgz |
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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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