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Graphical methods testing multivariate normality assumption. Methods including assessing score function, and moment generating functions,independent transformations and linear transformations. For more details see Tran (2024),"Contributions to Multivariate Data Science: Assessment and Identification of Multivariate Distributions and Supervised Learning for Groups of Objects." , PhD thesis, <https://our.oakland.edu/items/c8942577-2562-4d2f-8677-cb8ec0bf6234>.
Version: | 1.0.1 |
Depends: | R (≥ 3.5.0) |
Imports: | Rdpack, ggplot2, stats, Matrix, MatrixExtra, MASS, rlang |
Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0) |
Published: | 2025-03-25 |
Author: | Huong Tran |
Maintainer: | Huong Tran <quynhhuong5335 at gmail.com> |
License: | MIT + file LICENSE |
NeedsCompilation: | no |
Materials: | README NEWS |
CRAN checks: | PlotNormTest results |
Reference manual: | PlotNormTest.pdf |
Vignettes: |
intro-PlotNormTest (source, R code) |
Package source: | PlotNormTest_1.0.1.tar.gz |
Windows binaries: | r-devel: not available, r-release: not available, r-oldrel: not available |
macOS binaries: | r-devel (arm64): PlotNormTest_1.0.1.tgz, r-release (arm64): PlotNormTest_1.0.1.tgz, r-oldrel (arm64): PlotNormTest_1.0.1.tgz, r-devel (x86_64): PlotNormTest_1.0.1.tgz, r-release (x86_64): PlotNormTest_1.0.1.tgz, r-oldrel (x86_64): PlotNormTest_1.0.1.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.