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Provides a set of basic and extensible data structures and functions for multivariate analysis, including dimensionality reduction techniques, projection methods, and preprocessing functions. The aim of this package is to offer a flexible and user-friendly framework for multivariate analysis that can be easily extended for custom requirements and specific data analysis tasks.
Version: | 0.2.0 |
Imports: | rlang, chk, glmnet, corpcor, Matrix, purrr, rsvd, svd, pls, irlba, RSpectra, proxy, matrixStats, fitdistrplus |
Suggests: | covr, randomForest, testthat, magrittr, knitr, rmarkdown, MASS |
Published: | 2024-03-28 |
DOI: | 10.32614/CRAN.package.multivarious |
Author: | Bradley Buchsbaum [aut, cre] |
Maintainer: | Bradley Buchsbaum <brad.buchsbaum at gmail.com> |
License: | MIT + file LICENSE |
URL: | https://bbuchsbaum.github.io/multivarious/ |
NeedsCompilation: | no |
Materials: | README |
CRAN checks: | multivarious results |
Reference manual: | multivarious.pdf |
Vignettes: |
Introduction to the multivarious Package |
Package source: | multivarious_0.2.0.tar.gz |
Windows binaries: | r-devel: multivarious_0.2.0.zip, r-release: multivarious_0.2.0.zip, r-oldrel: multivarious_0.2.0.zip |
macOS binaries: | r-release (arm64): multivarious_0.2.0.tgz, r-oldrel (arm64): multivarious_0.2.0.tgz, r-release (x86_64): multivarious_0.2.0.tgz, r-oldrel (x86_64): multivarious_0.2.0.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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