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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
Suggests: ChemoSpec, chemometrics, knitr, tinytest, roxut, rmarkdown, plot3D, ade4, plotrix, latex2exp, plotly, xtable, bookdown
Published: 2024-04-26
DOI: 10.32614/CRAN.package.LearnPCA
Author: Bryan A. Hanson ORCID iD [aut, cre], David T. Harvey [aut]
Maintainer: Bryan A. Hanson <hanson at depauw.edu>
BugReports: https://github.com/bryanhanson/LearnPCA/issues
License: GPL-3
URL: https://bryanhanson.github.io/LearnPCA/
NeedsCompilation: no
Materials: NEWS
In views: ChemPhys
CRAN checks: LearnPCA results

Documentation:

Reference manual: LearnPCA.pdf
Vignettes: Vignette 01: A Guide to Learning PCA with LearnPCA (Start Here)
Vignette 02: A Conceptual Introduction to PCA
Vignette 03: Step-by-Step PCA
Vignette 04: Understanding Scores and Loadings
Vignette 05: Visualizing PCA in 3D
Vignette 06: The Math Behind PCA
Vignette 07: Functions for PCA
Vignette 08: Notes

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

Linking:

Please use the canonical form https://CRAN.R-project.org/package=LearnPCA to link to this page.

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.