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multivarious: Extensible Data Structures for Multivariate Analysis

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
Author: Bradley Buchsbaum ORCID iD [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

Documentation:

Reference manual: multivarious.pdf
Vignettes: Introduction to the multivarious Package

Downloads:

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

Linking:

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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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