LearnPCA: Functions, Data Sets and Vignettes to Aid in Learning Principal Components Analysis (PCA)

Principal component analysis (PCA) is one of the most widely used data analysis techniques. This package provides a series of vignettes explaining PCA starting from basic concepts. The primary purpose is to serve as a self-study resource for anyone wishing to understand PCA better. A few convenience functions are provided as well.

Version: 0.3.4
Depends: rpart, class, nnet
Imports: markdown, shiny, stats, graphics
Published: 2024年04月26日
Author: Bryan A. Hanson ORCID iD [aut, cre], David T. Harvey [aut]
Maintainer: Bryan A. Hanson <hanson at depauw.edu>
License: GPL-3
NeedsCompilation: no
Materials: NEWS
In views: ChemPhys
CRAN checks: LearnPCA results

Documentation:

Reference manual: LearnPCA.html , LearnPCA.pdf

Downloads:

Package source: LearnPCA_0.3.4.tar.gz
Windows binaries: r-devel: LearnPCA_0.3.4.zip, r-release: LearnPCA_0.3.4.zip, r-oldrel: LearnPCA_0.3.4.zip
macOS binaries: r-release (arm64): LearnPCA_0.3.4.tgz, r-oldrel (arm64): LearnPCA_0.3.4.tgz, r-release (x86_64): LearnPCA_0.3.4.tgz, r-oldrel (x86_64): LearnPCA_0.3.4.tgz
Old sources: LearnPCA archive

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